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Choosing the Right Research Methodology: A Guide for Researchers

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Choosing an optimal research methodology is crucial for the success of any research project. The methodology you select will determine the type of data you collect, how you collect it, and how you analyse it. Understanding the different types of research methods available along with their strengths and weaknesses, is thus imperative to make an informed decision.

Understanding different research methods:

There are several research methods available depending on the type of study you are conducting, i.e., whether it is laboratory-based, clinical, epidemiological, or survey based . Some common methodologies include qualitative research, quantitative research, experimental research, survey-based research, and action research. Each method can be opted for and modified, depending on the type of research hypotheses and objectives.

Qualitative vs quantitative research:

When deciding on a research methodology, one of the key factors to consider is whether your research will be qualitative or quantitative. Qualitative research is used to understand people’s experiences, concepts, thoughts, or behaviours . Quantitative research, on the contrary, deals with numbers, graphs, and charts, and is used to test or confirm hypotheses, assumptions, and theories. 

Qualitative research methodology:

Qualitative research is often used to examine issues that are not well understood, and to gather additional insights on these topics. Qualitative research methods include open-ended survey questions, observations of behaviours described through words, and reviews of literature that has explored similar theories and ideas. These methods are used to understand how language is used in real-world situations, identify common themes or overarching ideas, and describe and interpret various texts. Data analysis for qualitative research typically includes discourse analysis, thematic analysis, and textual analysis. 

Quantitative research methodology:

The goal of quantitative research is to test hypotheses, confirm assumptions and theories, and determine cause-and-effect relationships. Quantitative research methods include experiments, close-ended survey questions, and countable and numbered observations. Data analysis for quantitative research relies heavily on statistical methods.

Analysing qualitative vs quantitative data:

The methods used for data analysis also differ for qualitative and quantitative research. As mentioned earlier, quantitative data is generally analysed using statistical methods and does not leave much room for speculation. It is more structured and follows a predetermined plan. In quantitative research, the researcher starts with a hypothesis and uses statistical methods to test it. Contrarily, methods used for qualitative data analysis can identify patterns and themes within the data, rather than provide statistical measures of the data. It is an iterative process, where the researcher goes back and forth trying to gauge the larger implications of the data through different perspectives and revising the analysis if required.

When to use qualitative vs quantitative research:

The choice between qualitative and quantitative research will depend on the gap that the research project aims to address, and specific objectives of the study. If the goal is to establish facts about a subject or topic, quantitative research is an appropriate choice. However, if the goal is to understand people’s experiences or perspectives, qualitative research may be more suitable. 

Conclusion:

In conclusion, an understanding of the different research methods available, their applicability, advantages, and disadvantages is essential for making an informed decision on the best methodology for your project. If you need any additional guidance on which research methodology to opt for, you can head over to Elsevier Author Services (EAS). EAS experts will guide you throughout the process and help you choose the perfect methodology for your research goals.

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Research methods--quantitative, qualitative, and more: overview.

• Quantitative Research
• Qualitative Research
• Data Science Methods (Machine Learning, AI, Big Data)
• Text Mining and Computational Text Analysis
• Evidence Synthesis/Systematic Reviews
• Get Data, Get Help!

About Research Methods

This guide provides an overview of research methods, how to choose and use them, and supports and resources at UC Berkeley. 

As Patten and Newhart note in the book Understanding Research Methods , "Research methods are the building blocks of the scientific enterprise. They are the "how" for building systematic knowledge. The accumulation of knowledge through research is by its nature a collective endeavor. Each well-designed study provides evidence that may support, amend, refute, or deepen the understanding of existing knowledge...Decisions are important throughout the practice of research and are designed to help researchers collect evidence that includes the full spectrum of the phenomenon under study, to maintain logical rules, and to mitigate or account for possible sources of bias. In many ways, learning research methods is learning how to see and make these decisions."

The choice of methods varies by discipline, by the kind of phenomenon being studied and the data being used to study it, by the technology available, and more.  This guide is an introduction, but if you don't see what you need here, always contact your subject librarian, and/or take a look to see if there's a library research guide that will answer your question. 

Suggestions for changes and additions to this guide are welcome! 

START HERE: SAGE Research Methods

Without question, the most comprehensive resource available from the library is SAGE Research Methods.  HERE IS THE ONLINE GUIDE  to this one-stop shopping collection, and some helpful links are below:

• SAGE Research Methods
• Little Green Books  (Quantitative Methods)
• Little Blue Books  (Qualitative Methods)
• Dictionaries and Encyclopedias  
• Case studies of real research projects
• Sample datasets for hands-on practice
• Streaming video--see methods come to life
• Methodspace- -a community for researchers
• SAGE Research Methods Course Mapping

Library Data Services at UC Berkeley

Library Data Services Program and Digital Scholarship Services

The LDSP offers a variety of services and tools !  From this link, check out pages for each of the following topics:  discovering data, managing data, collecting data, GIS data, text data mining, publishing data, digital scholarship, open science, and the Research Data Management Program.

Be sure also to check out the visual guide to where to seek assistance on campus with any research question you may have!

Library GIS Services

Other Data Services at Berkeley

D-Lab Supports Berkeley faculty, staff, and graduate students with research in data intensive social science, including a wide range of training and workshop offerings Dryad Dryad is a simple self-service tool for researchers to use in publishing their datasets. It provides tools for the effective publication of and access to research data. Geospatial Innovation Facility (GIF) Provides leadership and training across a broad array of integrated mapping technologies on campu Research Data Management A UC Berkeley guide and consulting service for research data management issues

General Research Methods Resources

Here are some general resources for assistance:

• Assistance from ICPSR (must create an account to access): Getting Help with Data , and Resources for Students
• Wiley Stats Ref for background information on statistics topics
• Survey Documentation and Analysis (SDA) .  Program for easy web-based analysis of survey data.

Consultants

• D-Lab/Data Science Discovery Consultants Request help with your research project from peer consultants.
• Research data (RDM) consulting Meet with RDM consultants before designing the data security, storage, and sharing aspects of your qualitative project.
• Statistics Department Consulting Services A service in which advanced graduate students, under faculty supervision, are available to consult during specified hours in the Fall and Spring semesters.

Related Resourcex

• IRB / CPHS Qualitative research projects with human subjects often require that you go through an ethics review.
• OURS (Office of Undergraduate Research and Scholarships) OURS supports undergraduates who want to embark on research projects and assistantships. In particular, check out their "Getting Started in Research" workshops
• Sponsored Projects Sponsored projects works with researchers applying for major external grants.
• Next: Quantitative Research >>
• Last Updated: Apr 25, 2024 11:09 AM
• URL: https://guides.lib.berkeley.edu/researchmethods

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• Dissertation
• What Is a Research Methodology? | Steps & Tips

What Is a Research Methodology? | Steps & Tips

Published on 25 February 2019 by Shona McCombes . Revised on 10 October 2022.

Your research methodology discusses and explains the data collection and analysis methods you used in your research. A key part of your thesis, dissertation, or research paper, the methodology chapter explains what you did and how you did it, allowing readers to evaluate the reliability and validity of your research.

It should include:

• The type of research you conducted
• How you collected and analysed your data
• Any tools or materials you used in the research
• Why you chose these methods
• Your methodology section should generally be written in the past tense .
• Academic style guides in your field may provide detailed guidelines on what to include for different types of studies.
• Your citation style might provide guidelines for your methodology section (e.g., an APA Style methods section ).

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Table of contents

How to write a research methodology, why is a methods section important, step 1: explain your methodological approach, step 2: describe your data collection methods, step 3: describe your analysis method, step 4: evaluate and justify the methodological choices you made, tips for writing a strong methodology chapter, frequently asked questions about methodology.

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Your methods section is your opportunity to share how you conducted your research and why you chose the methods you chose. It’s also the place to show that your research was rigorously conducted and can be replicated .

It gives your research legitimacy and situates it within your field, and also gives your readers a place to refer to if they have any questions or critiques in other sections.

You can start by introducing your overall approach to your research. You have two options here.

Option 1: Start with your “what”

What research problem or question did you investigate?

• Aim to describe the characteristics of something?
• Explore an under-researched topic?
• Establish a causal relationship?

And what type of data did you need to achieve this aim?

• Quantitative data , qualitative data , or a mix of both?
• Primary data collected yourself, or secondary data collected by someone else?
• Experimental data gathered by controlling and manipulating variables, or descriptive data gathered via observations?

Option 2: Start with your “why”

Depending on your discipline, you can also start with a discussion of the rationale and assumptions underpinning your methodology. In other words, why did you choose these methods for your study?

• Why is this the best way to answer your research question?
• Is this a standard methodology in your field, or does it require justification?
• Were there any ethical considerations involved in your choices?
• What are the criteria for validity and reliability in this type of research ?

Once you have introduced your reader to your methodological approach, you should share full details about your data collection methods .

Quantitative methods

In order to be considered generalisable, you should describe quantitative research methods in enough detail for another researcher to replicate your study.

Here, explain how you operationalised your concepts and measured your variables. Discuss your sampling method or inclusion/exclusion criteria, as well as any tools, procedures, and materials you used to gather your data.

Surveys Describe where, when, and how the survey was conducted.

• How did you design the questionnaire?
• What form did your questions take (e.g., multiple choice, Likert scale )?
• Were your surveys conducted in-person or virtually?
• What sampling method did you use to select participants?
• What was your sample size and response rate?

Experiments Share full details of the tools, techniques, and procedures you used to conduct your experiment.

• How did you design the experiment ?
• How did you recruit participants?
• How did you manipulate and measure the variables ?
• What tools did you use?

Existing data Explain how you gathered and selected the material (such as datasets or archival data) that you used in your analysis.

• Where did you source the material?
• How was the data originally produced?
• What criteria did you use to select material (e.g., date range)?

The survey consisted of 5 multiple-choice questions and 10 questions measured on a 7-point Likert scale.

The goal was to collect survey responses from 350 customers visiting the fitness apparel company’s brick-and-mortar location in Boston on 4–8 July 2022, between 11:00 and 15:00.

Here, a customer was defined as a person who had purchased a product from the company on the day they took the survey. Participants were given 5 minutes to fill in the survey anonymously. In total, 408 customers responded, but not all surveys were fully completed. Due to this, 371 survey results were included in the analysis.

Qualitative methods

In qualitative research , methods are often more flexible and subjective. For this reason, it’s crucial to robustly explain the methodology choices you made.

Be sure to discuss the criteria you used to select your data, the context in which your research was conducted, and the role you played in collecting your data (e.g., were you an active participant, or a passive observer?)

Interviews or focus groups Describe where, when, and how the interviews were conducted.

• How did you find and select participants?
• How many participants took part?
• What form did the interviews take ( structured , semi-structured , or unstructured )?
• How long were the interviews?
• How were they recorded?

Participant observation Describe where, when, and how you conducted the observation or ethnography .

• What group or community did you observe? How long did you spend there?
• How did you gain access to this group? What role did you play in the community?
• How long did you spend conducting the research? Where was it located?
• How did you record your data (e.g., audiovisual recordings, note-taking)?

Existing data Explain how you selected case study materials for your analysis.

• What type of materials did you analyse?
• How did you select them?

In order to gain better insight into possibilities for future improvement of the fitness shop’s product range, semi-structured interviews were conducted with 8 returning customers.

Here, a returning customer was defined as someone who usually bought products at least twice a week from the store.

Surveys were used to select participants. Interviews were conducted in a small office next to the cash register and lasted approximately 20 minutes each. Answers were recorded by note-taking, and seven interviews were also filmed with consent. One interviewee preferred not to be filmed.

Mixed methods

Mixed methods research combines quantitative and qualitative approaches. If a standalone quantitative or qualitative study is insufficient to answer your research question, mixed methods may be a good fit for you.

Mixed methods are less common than standalone analyses, largely because they require a great deal of effort to pull off successfully. If you choose to pursue mixed methods, it’s especially important to robustly justify your methods here.

Next, you should indicate how you processed and analysed your data. Avoid going into too much detail: you should not start introducing or discussing any of your results at this stage.

In quantitative research , your analysis will be based on numbers. In your methods section, you can include:

• How you prepared the data before analysing it (e.g., checking for missing data , removing outliers , transforming variables)
• Which software you used (e.g., SPSS, Stata or R)
• Which statistical tests you used (e.g., two-tailed t test , simple linear regression )

In qualitative research, your analysis will be based on language, images, and observations (often involving some form of textual analysis ).

Specific methods might include:

• Content analysis : Categorising and discussing the meaning of words, phrases and sentences
• Thematic analysis : Coding and closely examining the data to identify broad themes and patterns
• Discourse analysis : Studying communication and meaning in relation to their social context

Mixed methods combine the above two research methods, integrating both qualitative and quantitative approaches into one coherent analytical process.

Above all, your methodology section should clearly make the case for why you chose the methods you did. This is especially true if you did not take the most standard approach to your topic. In this case, discuss why other methods were not suitable for your objectives, and show how this approach contributes new knowledge or understanding.

In any case, it should be overwhelmingly clear to your reader that you set yourself up for success in terms of your methodology’s design. Show how your methods should lead to results that are valid and reliable, while leaving the analysis of the meaning, importance, and relevance of your results for your discussion section .

• Quantitative: Lab-based experiments cannot always accurately simulate real-life situations and behaviours, but they are effective for testing causal relationships between variables .
• Qualitative: Unstructured interviews usually produce results that cannot be generalised beyond the sample group , but they provide a more in-depth understanding of participants’ perceptions, motivations, and emotions.
• Mixed methods: Despite issues systematically comparing differing types of data, a solely quantitative study would not sufficiently incorporate the lived experience of each participant, while a solely qualitative study would be insufficiently generalisable.

Remember that your aim is not just to describe your methods, but to show how and why you applied them. Again, it’s critical to demonstrate that your research was rigorously conducted and can be replicated.

1. Focus on your objectives and research questions

The methodology section should clearly show why your methods suit your objectives  and convince the reader that you chose the best possible approach to answering your problem statement and research questions .

2. Cite relevant sources

Your methodology can be strengthened by referencing existing research in your field. This can help you to:

• Show that you followed established practice for your type of research
• Discuss how you decided on your approach by evaluating existing research
• Present a novel methodological approach to address a gap in the literature

3. Write for your audience

Consider how much information you need to give, and avoid getting too lengthy. If you are using methods that are standard for your discipline, you probably don’t need to give a lot of background or justification.

Regardless, your methodology should be a clear, well-structured text that makes an argument for your approach, not just a list of technical details and procedures.

Methodology refers to the overarching strategy and rationale of your research. Developing your methodology involves studying the research methods used in your field and the theories or principles that underpin them, in order to choose the approach that best matches your objectives.

Methods are the specific tools and procedures you use to collect and analyse data (e.g. interviews, experiments , surveys , statistical tests ).

In a dissertation or scientific paper, the methodology chapter or methods section comes after the introduction and before the results , discussion and conclusion .

Depending on the length and type of document, you might also include a literature review or theoretical framework before the methodology.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

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What is research methodology?

The basics of research methodology

Why do you need a research methodology, what needs to be included, why do you need to document your research method, what are the different types of research instruments, qualitative / quantitative / mixed research methodologies, how do you choose the best research methodology for you, frequently asked questions about research methodology, related articles.

When you’re working on your first piece of academic research, there are many different things to focus on, and it can be overwhelming to stay on top of everything. This is especially true of budding or inexperienced researchers.

If you’ve never put together a research proposal before or find yourself in a position where you need to explain your research methodology decisions, there are a few things you need to be aware of.

Once you understand the ins and outs, handling academic research in the future will be less intimidating. We break down the basics below:

A research methodology encompasses the way in which you intend to carry out your research. This includes how you plan to tackle things like collection methods, statistical analysis, participant observations, and more.

You can think of your research methodology as being a formula. One part will be how you plan on putting your research into practice, and another will be why you feel this is the best way to approach it. Your research methodology is ultimately a methodological and systematic plan to resolve your research problem.

In short, you are explaining how you will take your idea and turn it into a study, which in turn will produce valid and reliable results that are in accordance with the aims and objectives of your research. This is true whether your paper plans to make use of qualitative methods or quantitative methods.

The purpose of a research methodology is to explain the reasoning behind your approach to your research - you'll need to support your collection methods, methods of analysis, and other key points of your work.

Think of it like writing a plan or an outline for you what you intend to do.

When carrying out research, it can be easy to go off-track or depart from your standard methodology.

Tip: Having a methodology keeps you accountable and on track with your original aims and objectives, and gives you a suitable and sound plan to keep your project manageable, smooth, and effective.

With all that said, how do you write out your standard approach to a research methodology?

As a general plan, your methodology should include the following information:

• Your research method.  You need to state whether you plan to use quantitative analysis, qualitative analysis, or mixed-method research methods. This will often be determined by what you hope to achieve with your research.
• Explain your reasoning. Why are you taking this methodological approach? Why is this particular methodology the best way to answer your research problem and achieve your objectives?
• Explain your instruments.  This will mainly be about your collection methods. There are varying instruments to use such as interviews, physical surveys, questionnaires, for example. Your methodology will need to detail your reasoning in choosing a particular instrument for your research.
• What will you do with your results?  How are you going to analyze the data once you have gathered it?
• Advise your reader.  If there is anything in your research methodology that your reader might be unfamiliar with, you should explain it in more detail. For example, you should give any background information to your methods that might be relevant or provide your reasoning if you are conducting your research in a non-standard way.
• How will your sampling process go?  What will your sampling procedure be and why? For example, if you will collect data by carrying out semi-structured or unstructured interviews, how will you choose your interviewees and how will you conduct the interviews themselves?
• Any practical limitations?  You should discuss any limitations you foresee being an issue when you’re carrying out your research.

In any dissertation, thesis, or academic journal, you will always find a chapter dedicated to explaining the research methodology of the person who carried out the study, also referred to as the methodology section of the work.

A good research methodology will explain what you are going to do and why, while a poor methodology will lead to a messy or disorganized approach.

You should also be able to justify in this section your reasoning for why you intend to carry out your research in a particular way, especially if it might be a particularly unique method.

Having a sound methodology in place can also help you with the following:

• When another researcher at a later date wishes to try and replicate your research, they will need your explanations and guidelines.
• In the event that you receive any criticism or questioning on the research you carried out at a later point, you will be able to refer back to it and succinctly explain the how and why of your approach.
• It provides you with a plan to follow throughout your research. When you are drafting your methodology approach, you need to be sure that the method you are using is the right one for your goal. This will help you with both explaining and understanding your method.
• It affords you the opportunity to document from the outset what you intend to achieve with your research, from start to finish.

A research instrument is a tool you will use to help you collect, measure and analyze the data you use as part of your research.

The choice of research instrument will usually be yours to make as the researcher and will be whichever best suits your methodology.

There are many different research instruments you can use in collecting data for your research.

Generally, they can be grouped as follows:

• Interviews (either as a group or one-on-one). You can carry out interviews in many different ways. For example, your interview can be structured, semi-structured, or unstructured. The difference between them is how formal the set of questions is that is asked of the interviewee. In a group interview, you may choose to ask the interviewees to give you their opinions or perceptions on certain topics.
• Surveys (online or in-person). In survey research, you are posing questions in which you ask for a response from the person taking the survey. You may wish to have either free-answer questions such as essay-style questions, or you may wish to use closed questions such as multiple choice. You may even wish to make the survey a mixture of both.
• Focus Groups.  Similar to the group interview above, you may wish to ask a focus group to discuss a particular topic or opinion while you make a note of the answers given.
• Observations.  This is a good research instrument to use if you are looking into human behaviors. Different ways of researching this include studying the spontaneous behavior of participants in their everyday life, or something more structured. A structured observation is research conducted at a set time and place where researchers observe behavior as planned and agreed upon with participants.

These are the most common ways of carrying out research, but it is really dependent on your needs as a researcher and what approach you think is best to take.

It is also possible to combine a number of research instruments if this is necessary and appropriate in answering your research problem.

There are three different types of methodologies, and they are distinguished by whether they focus on words, numbers, or both.

➡️ Want to learn more about the differences between qualitative and quantitative research, and how to use both methods? Check out our guide for that!

If you've done your due diligence, you'll have an idea of which methodology approach is best suited to your research.

It’s likely that you will have carried out considerable reading and homework before you reach this point and you may have taken inspiration from other similar studies that have yielded good results.

Still, it is important to consider different options before setting your research in stone. Exploring different options available will help you to explain why the choice you ultimately make is preferable to other methods.

If proving your research problem requires you to gather large volumes of numerical data to test hypotheses, a quantitative research method is likely to provide you with the most usable results.

If instead you’re looking to try and learn more about people, and their perception of events, your methodology is more exploratory in nature and would therefore probably be better served using a qualitative research methodology.

It helps to always bring things back to the question: what do I want to achieve with my research?

Once you have conducted your research, you need to analyze it. Here are some helpful guides for qualitative data analysis:

➡️  How to do a content analysis

➡️  How to do a thematic analysis

➡️  How to do a rhetorical analysis

Research methodology refers to the techniques used to find and analyze information for a study, ensuring that the results are valid, reliable and that they address the research objective.

Data can typically be organized into four different categories or methods: observational, experimental, simulation, and derived.

Writing a methodology section is a process of introducing your methods and instruments, discussing your analysis, providing more background information, addressing your research limitations, and more.

Your research methodology section will need a clear research question and proposed research approach. You'll need to add a background, introduce your research question, write your methodology and add the works you cited during your data collecting phase.

The research methodology section of your study will indicate how valid your findings are and how well-informed your paper is. It also assists future researchers planning to use the same methodology, who want to cite your study or replicate it.

How To Choose Your Research Methodology

Qualitative vs quantitative vs mixed methods.

By: Derek Jansen (MBA). Expert Reviewed By: Dr Eunice Rautenbach | June 2021

Without a doubt, one of the most common questions we receive at Grad Coach is “ How do I choose the right methodology for my research? ”. It’s easy to see why – with so many options on the research design table, it’s easy to get intimidated, especially with all the complex lingo!

In this post, we’ll explain the three overarching types of research – qualitative, quantitative and mixed methods – and how you can go about choosing the best methodological approach for your research.

Overview: Choosing Your Methodology

Understanding the options – Qualitative research – Quantitative research – Mixed methods-based research

Choosing a research methodology – Nature of the research – Research area norms – Practicalities

1. Understanding the options

Before we jump into the question of how to choose a research methodology, it’s useful to take a step back to understand the three overarching types of research – qualitative , quantitative and mixed methods -based research. Each of these options takes a different methodological approach.

Qualitative research utilises data that is not numbers-based. In other words, qualitative research focuses on words , descriptions , concepts or ideas – while quantitative research makes use of numbers and statistics. Qualitative research investigates the “softer side” of things to explore and describe, while quantitative research focuses on the “hard numbers”, to measure differences between variables and the relationships between them.

Importantly, qualitative research methods are typically used to explore and gain a deeper understanding of the complexity of a situation – to draw a rich picture . In contrast to this, quantitative methods are usually used to confirm or test hypotheses . In other words, they have distinctly different purposes. The table below highlights a few of the key differences between qualitative and quantitative research – you can learn more about the differences here.

• Uses an inductive approach
• Is used to build theories
• Takes a subjective approach
• Adopts an open and flexible approach
• The researcher is close to the respondents
• Interviews and focus groups are oftentimes used to collect word-based data.
• Generally, draws on small sample sizes
• Uses qualitative data analysis techniques (e.g. content analysis , thematic analysis , etc)
• Uses a deductive approach
• Is used to test theories
• Takes an objective approach
• Adopts a closed, highly planned approach
• The research is disconnected from respondents
• Surveys or laboratory equipment are often used to collect number-based data.
• Generally, requires large sample sizes
• Uses statistical analysis techniques to make sense of the data

Mixed methods -based research, as you’d expect, attempts to bring these two types of research together, drawing on both qualitative and quantitative data. Quite often, mixed methods-based studies will use qualitative research to explore a situation and develop a potential model of understanding (this is called a conceptual framework), and then go on to use quantitative methods to test that model empirically.

In other words, while qualitative and quantitative methods (and the philosophies that underpin them) are completely different, they are not at odds with each other. It’s not a competition of qualitative vs quantitative. On the contrary, they can be used together to develop a high-quality piece of research. Of course, this is easier said than done, so we usually recommend that first-time researchers stick to a single approach , unless the nature of their study truly warrants a mixed-methods approach.

The key takeaway here, and the reason we started by looking at the three options, is that it’s important to understand that each methodological approach has a different purpose – for example, to explore and understand situations (qualitative), to test and measure (quantitative) or to do both. They’re not simply alternative tools for the same job. 

Right – now that we’ve got that out of the way, let’s look at how you can go about choosing the right methodology for your research.

2. How to choose a research methodology

To choose the right research methodology for your dissertation or thesis, you need to consider three important factors . Based on these three factors, you can decide on your overarching approach – qualitative, quantitative or mixed methods. Once you’ve made that decision, you can flesh out the finer details of your methodology, such as the sampling , data collection methods and analysis techniques (we discuss these separately in other posts ).

The three factors you need to consider are:

• The nature of your research aims, objectives and research questions
• The methodological approaches taken in the existing literature
• Practicalities and constraints

Let’s take a look at each of these.

Factor #1: The nature of your research

As I mentioned earlier, each type of research (and therefore, research methodology), whether qualitative, quantitative or mixed, has a different purpose and helps solve a different type of question. So, it’s logical that the key deciding factor in terms of which research methodology you adopt is the nature of your research aims, objectives and research questions .

But, what types of research exist?

Broadly speaking, research can fall into one of three categories:

• Exploratory – getting a better understanding of an issue and potentially developing a theory regarding it
• Confirmatory – confirming a potential theory or hypothesis by testing it empirically
• A mix of both – building a potential theory or hypothesis and then testing it

As a rule of thumb, exploratory research tends to adopt a qualitative approach , whereas confirmatory research tends to use quantitative methods . This isn’t set in stone, but it’s a very useful heuristic. Naturally then, research that combines a mix of both, or is seeking to develop a theory from the ground up and then test that theory, would utilize a mixed-methods approach.

Let’s look at an example in action.

If your research aims were to understand the perspectives of war veterans regarding certain political matters, you’d likely adopt a qualitative methodology, making use of interviews to collect data and one or more qualitative data analysis methods to make sense of the data.

If, on the other hand, your research aims involved testing a set of hypotheses regarding the link between political leaning and income levels, you’d likely adopt a quantitative methodology, using numbers-based data from a survey to measure the links between variables and/or constructs .

So, the first (and most important thing) thing you need to consider when deciding which methodological approach to use for your research project is the nature of your research aims , objectives and research questions. Specifically, you need to assess whether your research leans in an exploratory or confirmatory direction or involves a mix of both.

The importance of achieving solid alignment between these three factors and your methodology can’t be overstated. If they’re misaligned, you’re going to be forcing a square peg into a round hole. In other words, you’ll be using the wrong tool for the job, and your research will become a disjointed mess.

If your research is a mix of both exploratory and confirmatory, but you have a tight word count limit, you may need to consider trimming down the scope a little and focusing on one or the other. One methodology executed well has a far better chance of earning marks than a poorly executed mixed methods approach. So, don’t try to be a hero, unless there is a very strong underpinning logic.

Need a helping hand?

Factor #2: The disciplinary norms

Choosing the right methodology for your research also involves looking at the approaches used by other researchers in the field, and studies with similar research aims and objectives to yours. Oftentimes, within a discipline, there is a common methodological approach (or set of approaches) used in studies. While this doesn’t mean you should follow the herd “just because”, you should at least consider these approaches and evaluate their merit within your context.

A major benefit of reviewing the research methodologies used by similar studies in your field is that you can often piggyback on the data collection techniques that other (more experienced) researchers have developed. For example, if you’re undertaking a quantitative study, you can often find tried and tested survey scales with high Cronbach’s alphas. These are usually included in the appendices of journal articles, so you don’t even have to contact the original authors. By using these, you’ll save a lot of time and ensure that your study stands on the proverbial “shoulders of giants” by using high-quality measurement instruments .

Of course, when reviewing existing literature, keep point #1 front of mind. In other words, your methodology needs to align with your research aims, objectives and questions. Don’t fall into the trap of adopting the methodological “norm” of other studies just because it’s popular. Only adopt that which is relevant to your research.

Factor #3: Practicalities

When choosing a research methodology, there will always be a tension between doing what’s theoretically best (i.e., the most scientifically rigorous research design ) and doing what’s practical , given your constraints . This is the nature of doing research and there are always trade-offs, as with anything else.

But what constraints, you ask?

When you’re evaluating your methodological options, you need to consider the following constraints:

• Data access
• Equipment and software
• Your knowledge and skills

Let’s look at each of these.

Constraint #1: Data access

The first practical constraint you need to consider is your access to data . If you’re going to be undertaking primary research , you need to think critically about the sample of respondents you realistically have access to. For example, if you plan to use in-person interviews , you need to ask yourself how many people you’ll need to interview, whether they’ll be agreeable to being interviewed, where they’re located, and so on.

If you’re wanting to undertake a quantitative approach using surveys to collect data, you’ll need to consider how many responses you’ll require to achieve statistically significant results. For many statistical tests, a sample of a few hundred respondents is typically needed to develop convincing conclusions.

So, think carefully about what data you’ll need access to, how much data you’ll need and how you’ll collect it. The last thing you want is to spend a huge amount of time on your research only to find that you can’t get access to the required data.

Constraint #2: Time

The next constraint is time. If you’re undertaking research as part of a PhD, you may have a fairly open-ended time limit, but this is unlikely to be the case for undergrad and Masters-level projects. So, pay attention to your timeline, as the data collection and analysis components of different methodologies have a major impact on time requirements . Also, keep in mind that these stages of the research often take a lot longer than originally anticipated.

Another practical implication of time limits is that it will directly impact which time horizon you can use – i.e. longitudinal vs cross-sectional . For example, if you’ve got a 6-month limit for your entire research project, it’s quite unlikely that you’ll be able to adopt a longitudinal time horizon. 

Constraint #3: Money

As with so many things, money is another important constraint you’ll need to consider when deciding on your research methodology. While some research designs will cost near zero to execute, others may require a substantial budget .

Some of the costs that may arise include:

• Software costs – e.g. survey hosting services, analysis software, etc.
• Promotion costs – e.g. advertising a survey to attract respondents
• Incentive costs – e.g. providing a prize or cash payment incentive to attract respondents
• Equipment rental costs – e.g. recording equipment, lab equipment, etc.
• Travel costs
• Food & beverages

These are just a handful of costs that can creep into your research budget. Like most projects, the actual costs tend to be higher than the estimates, so be sure to err on the conservative side and expect the unexpected. It’s critically important that you’re honest with yourself about these costs, or you could end up getting stuck midway through your project because you’ve run out of money.

Constraint #4: Equipment & software

Another practical consideration is the hardware and/or software you’ll need in order to undertake your research. Of course, this variable will depend on the type of data you’re collecting and analysing. For example, you may need lab equipment to analyse substances, or you may need specific analysis software to analyse statistical data. So, be sure to think about what hardware and/or software you’ll need for each potential methodological approach, and whether you have access to these.

Constraint #5: Your knowledge and skillset

The final practical constraint is a big one. Naturally, the research process involves a lot of learning and development along the way, so you will accrue knowledge and skills as you progress. However, when considering your methodological options, you should still consider your current position on the ladder.

Some of the questions you should ask yourself are:

• Am I more of a “numbers person” or a “words person”?
• How much do I know about the analysis methods I’ll potentially use (e.g. statistical analysis)?
• How much do I know about the software and/or hardware that I’ll potentially use?
• How excited am I to learn new research skills and gain new knowledge?
• How much time do I have to learn the things I need to learn?

Answering these questions honestly will provide you with another set of criteria against which you can evaluate the research methodology options you’ve shortlisted.

So, as you can see, there is a wide range of practicalities and constraints that you need to take into account when you’re deciding on a research methodology. These practicalities create a tension between the “ideal” methodology and the methodology that you can realistically pull off. This is perfectly normal, and it’s your job to find the option that presents the best set of trade-offs.

Recap: Choosing a methodology

In this post, we’ve discussed how to go about choosing a research methodology. The three major deciding factors we looked at were:

• Exploratory
• Confirmatory
• Combination
• Research area norms
• Hardware and software
• Your knowledge and skillset

If you have any questions, feel free to leave a comment below. If you’d like a helping hand with your research methodology, check out our 1-on-1 research coaching service , or book a free consultation with a friendly Grad Coach.

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This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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Very useful and informative especially for beginners

Nice article! I’m a beginner in the field of cybersecurity research. I am a Telecom and Network Engineer and Also aiming for PhD scholarship.

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Hi I am Anna ,

I am a PHD candidate in the area of cyber security, maybe we can link up

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I found the post very informative and practical.

I struggle so much with designs of the research for sure!

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Home » Research Project – Definition, Writing Guide and Ideas

Research Project – Definition, Writing Guide and Ideas

Table of Contents

Research Project

Definition :

Research Project is a planned and systematic investigation into a specific area of interest or problem, with the goal of generating new knowledge, insights, or solutions. It typically involves identifying a research question or hypothesis, designing a study to test it, collecting and analyzing data, and drawing conclusions based on the findings.

Types of Research Project

Types of Research Projects are as follows:

Basic Research

This type of research focuses on advancing knowledge and understanding of a subject area or phenomenon, without any specific application or practical use in mind. The primary goal is to expand scientific or theoretical knowledge in a particular field.

Applied Research

Applied research is aimed at solving practical problems or addressing specific issues. This type of research seeks to develop solutions or improve existing products, services or processes.

Action Research

Action research is conducted by practitioners and aimed at solving specific problems or improving practices in a particular context. It involves collaboration between researchers and practitioners, and often involves iterative cycles of data collection and analysis, with the goal of improving practices.

Quantitative Research

This type of research uses numerical data to investigate relationships between variables or to test hypotheses. It typically involves large-scale data collection through surveys, experiments, or secondary data analysis.

Qualitative Research

Qualitative research focuses on understanding and interpreting phenomena from the perspective of the people involved. It involves collecting and analyzing data in the form of text, images, or other non-numerical forms.

Mixed Methods Research

Mixed methods research combines elements of both quantitative and qualitative research, using multiple data sources and methods to gain a more comprehensive understanding of a phenomenon.

Longitudinal Research

This type of research involves studying a group of individuals or phenomena over an extended period of time, often years or decades. It is useful for understanding changes and developments over time.

Case Study Research

Case study research involves in-depth investigation of a particular case or phenomenon, often within a specific context. It is useful for understanding complex phenomena in their real-life settings.

Participatory Research

Participatory research involves active involvement of the people or communities being studied in the research process. It emphasizes collaboration, empowerment, and the co-production of knowledge.

Research Project Methodology

Research Project Methodology refers to the process of conducting research in an organized and systematic manner to answer a specific research question or to test a hypothesis. A well-designed research project methodology ensures that the research is rigorous, valid, and reliable, and that the findings are meaningful and can be used to inform decision-making.

There are several steps involved in research project methodology, which are described below:

Define the Research Question

The first step in any research project is to clearly define the research question or problem. This involves identifying the purpose of the research, the scope of the research, and the key variables that will be studied.

Develop a Research Plan

Once the research question has been defined, the next step is to develop a research plan. This plan outlines the methodology that will be used to collect and analyze data, including the research design, sampling strategy, data collection methods, and data analysis techniques.

Collect Data

The data collection phase involves gathering information through various methods, such as surveys, interviews, observations, experiments, or secondary data analysis. The data collected should be relevant to the research question and should be of sufficient quantity and quality to enable meaningful analysis.

Analyze Data

Once the data has been collected, it is analyzed using appropriate statistical techniques or other methods. The analysis should be guided by the research question and should aim to identify patterns, trends, relationships, or other insights that can inform the research findings.

Interpret and Report Findings

The final step in the research project methodology is to interpret the findings and report them in a clear and concise manner. This involves summarizing the results, discussing their implications, and drawing conclusions that can be used to inform decision-making.

Research Project Writing Guide

Here are some guidelines to help you in writing a successful research project:

• Choose a topic: Choose a topic that you are interested in and that is relevant to your field of study. It is important to choose a topic that is specific and focused enough to allow for in-depth research and analysis.
• Conduct a literature review : Conduct a thorough review of the existing research on your topic. This will help you to identify gaps in the literature and to develop a research question or hypothesis.
• Develop a research question or hypothesis : Based on your literature review, develop a clear research question or hypothesis that you will investigate in your study.
• Design your study: Choose an appropriate research design and methodology to answer your research question or test your hypothesis. This may include choosing a sample, selecting measures or instruments, and determining data collection methods.
• Collect data: Collect data using your chosen methods and instruments. Be sure to follow ethical guidelines and obtain informed consent from participants if necessary.
• Analyze data: Analyze your data using appropriate statistical or qualitative methods. Be sure to clearly report your findings and provide interpretations based on your research question or hypothesis.
• Discuss your findings : Discuss your findings in the context of the existing literature and your research question or hypothesis. Identify any limitations or implications of your study and suggest directions for future research.
• Write your project: Write your research project in a clear and organized manner, following the appropriate format and style guidelines for your field of study. Be sure to include an introduction, literature review, methodology, results, discussion, and conclusion.
• Revise and edit: Revise and edit your project for clarity, coherence, and accuracy. Be sure to proofread for spelling, grammar, and formatting errors.
• Cite your sources: Cite your sources accurately and appropriately using the appropriate citation style for your field of study.

Examples of Research Projects

Some Examples of Research Projects are as follows:

• Investigating the effects of a new medication on patients with a particular disease or condition.
• Exploring the impact of exercise on mental health and well-being.
• Studying the effectiveness of a new teaching method in improving student learning outcomes.
• Examining the impact of social media on political participation and engagement.
• Investigating the efficacy of a new therapy for a specific mental health disorder.
• Exploring the use of renewable energy sources in reducing carbon emissions and mitigating climate change.
• Studying the effects of a new agricultural technique on crop yields and environmental sustainability.
• Investigating the effectiveness of a new technology in improving business productivity and efficiency.
• Examining the impact of a new public policy on social inequality and access to resources.
• Exploring the factors that influence consumer behavior in a specific market.

Characteristics of Research Project

Here are some of the characteristics that are often associated with research projects:

• Clear objective: A research project is designed to answer a specific question or solve a particular problem. The objective of the research should be clearly defined from the outset.
• Systematic approach: A research project is typically carried out using a structured and systematic approach that involves careful planning, data collection, analysis, and interpretation.
• Rigorous methodology: A research project should employ a rigorous methodology that is appropriate for the research question being investigated. This may involve the use of statistical analysis, surveys, experiments, or other methods.
• Data collection : A research project involves collecting data from a variety of sources, including primary sources (such as surveys or experiments) and secondary sources (such as published literature or databases).
• Analysis and interpretation : Once the data has been collected, it needs to be analyzed and interpreted. This involves using statistical techniques or other methods to identify patterns or relationships in the data.
• Conclusion and implications : A research project should lead to a clear conclusion that answers the research question. It should also identify the implications of the findings for future research or practice.
• Communication: The results of the research project should be communicated clearly and effectively, using appropriate language and visual aids, to a range of audiences, including peers, stakeholders, and the wider public.

Importance of Research Project

Research projects are an essential part of the process of generating new knowledge and advancing our understanding of various fields of study. Here are some of the key reasons why research projects are important:

• Advancing knowledge : Research projects are designed to generate new knowledge and insights into particular topics or questions. This knowledge can be used to inform policies, practices, and decision-making processes across a range of fields.
• Solving problems: Research projects can help to identify solutions to real-world problems by providing a better understanding of the causes and effects of particular issues.
• Developing new technologies: Research projects can lead to the development of new technologies or products that can improve people’s lives or address societal challenges.
• Improving health outcomes: Research projects can contribute to improving health outcomes by identifying new treatments, diagnostic tools, or preventive strategies.
• Enhancing education: Research projects can enhance education by providing new insights into teaching and learning methods, curriculum development, and student learning outcomes.
• Informing public policy : Research projects can inform public policy by providing evidence-based recommendations and guidance on issues related to health, education, environment, social justice, and other areas.
• Enhancing professional development : Research projects can enhance the professional development of researchers by providing opportunities to develop new skills, collaborate with colleagues, and share knowledge with others.

Research Project Ideas

Following are some Research Project Ideas:

Field: Psychology

• Investigating the impact of social support on coping strategies among individuals with chronic illnesses.
• Exploring the relationship between childhood trauma and adult attachment styles.
• Examining the effects of exercise on cognitive function and brain health in older adults.
• Investigating the impact of sleep deprivation on decision making and risk-taking behavior.
• Exploring the relationship between personality traits and leadership styles in the workplace.
• Examining the effectiveness of cognitive-behavioral therapy (CBT) for treating anxiety disorders.
• Investigating the relationship between social comparison and body dissatisfaction in young women.
• Exploring the impact of parenting styles on children’s emotional regulation and behavior.
• Investigating the effectiveness of mindfulness-based interventions for treating depression.
• Examining the relationship between childhood adversity and later-life health outcomes.

Field: Economics

• Analyzing the impact of trade agreements on economic growth in developing countries.
• Examining the effects of tax policy on income distribution and poverty reduction.
• Investigating the relationship between foreign aid and economic development in low-income countries.
• Exploring the impact of globalization on labor markets and job displacement.
• Analyzing the impact of minimum wage laws on employment and income levels.
• Investigating the effectiveness of monetary policy in managing inflation and unemployment.
• Examining the relationship between economic freedom and entrepreneurship.
• Analyzing the impact of income inequality on social mobility and economic opportunity.
• Investigating the role of education in economic development.
• Examining the effectiveness of different healthcare financing systems in promoting health equity.

Field: Sociology

• Investigating the impact of social media on political polarization and civic engagement.
• Examining the effects of neighborhood characteristics on health outcomes.
• Analyzing the impact of immigration policies on social integration and cultural diversity.
• Investigating the relationship between social support and mental health outcomes in older adults.
• Exploring the impact of income inequality on social cohesion and trust.
• Analyzing the effects of gender and race discrimination on career advancement and pay equity.
• Investigating the relationship between social networks and health behaviors.
• Examining the effectiveness of community-based interventions for reducing crime and violence.
• Analyzing the impact of social class on cultural consumption and taste.
• Investigating the relationship between religious affiliation and social attitudes.

Field: Computer Science

• Developing an algorithm for detecting fake news on social media.
• Investigating the effectiveness of different machine learning algorithms for image recognition.
• Developing a natural language processing tool for sentiment analysis of customer reviews.
• Analyzing the security implications of blockchain technology for online transactions.
• Investigating the effectiveness of different recommendation algorithms for personalized advertising.
• Developing an artificial intelligence chatbot for mental health counseling.
• Investigating the effectiveness of different algorithms for optimizing online advertising campaigns.
• Developing a machine learning model for predicting consumer behavior in online marketplaces.
• Analyzing the privacy implications of different data sharing policies for online platforms.
• Investigating the effectiveness of different algorithms for predicting stock market trends.

Field: Education

• Investigating the impact of teacher-student relationships on academic achievement.
• Analyzing the effectiveness of different pedagogical approaches for promoting student engagement and motivation.
• Examining the effects of school choice policies on academic achievement and social mobility.
• Investigating the impact of technology on learning outcomes and academic achievement.
• Analyzing the effects of school funding disparities on educational equity and achievement gaps.
• Investigating the relationship between school climate and student mental health outcomes.
• Examining the effectiveness of different teaching strategies for promoting critical thinking and problem-solving skills.
• Investigating the impact of social-emotional learning programs on student behavior and academic achievement.
• Analyzing the effects of standardized testing on student motivation and academic achievement.

Field: Environmental Science

• Investigating the impact of climate change on species distribution and biodiversity.
• Analyzing the effectiveness of different renewable energy technologies in reducing carbon emissions.
• Examining the impact of air pollution on human health outcomes.
• Investigating the relationship between urbanization and deforestation in developing countries.
• Analyzing the effects of ocean acidification on marine ecosystems and biodiversity.
• Investigating the impact of land use change on soil fertility and ecosystem services.
• Analyzing the effectiveness of different conservation policies and programs for protecting endangered species and habitats.
• Investigating the relationship between climate change and water resources in arid regions.
• Examining the impact of plastic pollution on marine ecosystems and biodiversity.
• Investigating the effects of different agricultural practices on soil health and nutrient cycling.

Field: Linguistics

• Analyzing the impact of language diversity on social integration and cultural identity.
• Investigating the relationship between language and cognition in bilingual individuals.
• Examining the effects of language contact and language change on linguistic diversity.
• Investigating the role of language in shaping cultural norms and values.
• Analyzing the effectiveness of different language teaching methodologies for second language acquisition.
• Investigating the relationship between language proficiency and academic achievement.
• Examining the impact of language policy on language use and language attitudes.
• Investigating the role of language in shaping gender and social identities.
• Analyzing the effects of dialect contact on language variation and change.
• Investigating the relationship between language and emotion expression.

Field: Political Science

• Analyzing the impact of electoral systems on women’s political representation.
• Investigating the relationship between political ideology and attitudes towards immigration.
• Examining the effects of political polarization on democratic institutions and political stability.
• Investigating the impact of social media on political participation and civic engagement.
• Analyzing the effects of authoritarianism on human rights and civil liberties.
• Investigating the relationship between public opinion and foreign policy decisions.
• Examining the impact of international organizations on global governance and cooperation.
• Investigating the effectiveness of different conflict resolution strategies in resolving ethnic and religious conflicts.
• Analyzing the effects of corruption on economic development and political stability.
• Investigating the role of international law in regulating global governance and human rights.

Field: Medicine

• Investigating the impact of lifestyle factors on chronic disease risk and prevention.
• Examining the effectiveness of different treatment approaches for mental health disorders.
• Investigating the relationship between genetics and disease susceptibility.
• Analyzing the effects of social determinants of health on health outcomes and health disparities.
• Investigating the impact of different healthcare delivery models on patient outcomes and cost effectiveness.
• Examining the effectiveness of different prevention and treatment strategies for infectious diseases.
• Investigating the relationship between healthcare provider communication skills and patient satisfaction and outcomes.
• Analyzing the effects of medical error and patient safety on healthcare quality and outcomes.
• Investigating the impact of different pharmaceutical pricing policies on access to essential medicines.
• Examining the effectiveness of different rehabilitation approaches for improving function and quality of life in individuals with disabilities.

Field: Anthropology

• Analyzing the impact of colonialism on indigenous cultures and identities.
• Investigating the relationship between cultural practices and health outcomes in different populations.
• Examining the effects of globalization on cultural diversity and cultural exchange.
• Investigating the role of language in cultural transmission and preservation.
• Analyzing the effects of cultural contact on cultural change and adaptation.
• Investigating the impact of different migration policies on immigrant integration and acculturation.
• Examining the role of gender and sexuality in cultural norms and values.
• Investigating the impact of cultural heritage preservation on tourism and economic development.
• Analyzing the effects of cultural revitalization movements on indigenous communities.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Research Methods Guide: Research Design & Method

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Research Methods (sociology-focused)

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FAQ: Research Design & Method

What is the difference between Research Design and Research Method?

Research design is a plan to answer your research question.  A research method is a strategy used to implement that plan.  Research design and methods are different but closely related, because good research design ensures that the data you obtain will help you answer your research question more effectively.

Which research method should I choose ?

It depends on your research goal.  It depends on what subjects (and who) you want to study.  Let's say you are interested in studying what makes people happy, or why some students are more conscious about recycling on campus.  To answer these questions, you need to make a decision about how to collect your data.  Most frequently used methods include:

• Observation / Participant Observation
• Focus Groups
• Experiments
• Secondary Data Analysis / Archival Study
• Mixed Methods (combination of some of the above)

One particular method could be better suited to your research goal than others, because the data you collect from different methods will be different in quality and quantity.   For instance, surveys are usually designed to produce relatively short answers, rather than the extensive responses expected in qualitative interviews.

What other factors should I consider when choosing one method over another?

Time for data collection and analysis is something you want to consider.  An observation or interview method, so-called qualitative approach, helps you collect richer information, but it takes time.  Using a survey helps you collect more data quickly, yet it may lack details.  So, you will need to consider the time you have for research and the balance between strengths and weaknesses associated with each method (e.g., qualitative vs. quantitative).

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What is Research Methodology? Definition, Types, and Examples

Research methodology 1,2 is a structured and scientific approach used to collect, analyze, and interpret quantitative or qualitative data to answer research questions or test hypotheses. A research methodology is like a plan for carrying out research and helps keep researchers on track by limiting the scope of the research. Several aspects must be considered before selecting an appropriate research methodology, such as research limitations and ethical concerns that may affect your research.

The research methodology section in a scientific paper describes the different methodological choices made, such as the data collection and analysis methods, and why these choices were selected. The reasons should explain why the methods chosen are the most appropriate to answer the research question. A good research methodology also helps ensure the reliability and validity of the research findings. There are three types of research methodology—quantitative, qualitative, and mixed-method, which can be chosen based on the research objectives.

What is research methodology ?

A research methodology describes the techniques and procedures used to identify and analyze information regarding a specific research topic. It is a process by which researchers design their study so that they can achieve their objectives using the selected research instruments. It includes all the important aspects of research, including research design, data collection methods, data analysis methods, and the overall framework within which the research is conducted. While these points can help you understand what is research methodology, you also need to know why it is important to pick the right methodology.

Why is research methodology important?

Having a good research methodology in place has the following advantages: 3

• Helps other researchers who may want to replicate your research; the explanations will be of benefit to them.
• You can easily answer any questions about your research if they arise at a later stage.
• A research methodology provides a framework and guidelines for researchers to clearly define research questions, hypotheses, and objectives.
• It helps researchers identify the most appropriate research design, sampling technique, and data collection and analysis methods.
• A sound research methodology helps researchers ensure that their findings are valid and reliable and free from biases and errors.
• It also helps ensure that ethical guidelines are followed while conducting research.
• A good research methodology helps researchers in planning their research efficiently, by ensuring optimum usage of their time and resources.

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Types of research methodology.

There are three types of research methodology based on the type of research and the data required. 1

• Quantitative research methodology focuses on measuring and testing numerical data. This approach is good for reaching a large number of people in a short amount of time. This type of research helps in testing the causal relationships between variables, making predictions, and generalizing results to wider populations.
• Qualitative research methodology examines the opinions, behaviors, and experiences of people. It collects and analyzes words and textual data. This research methodology requires fewer participants but is still more time consuming because the time spent per participant is quite large. This method is used in exploratory research where the research problem being investigated is not clearly defined.
• Mixed-method research methodology uses the characteristics of both quantitative and qualitative research methodologies in the same study. This method allows researchers to validate their findings, verify if the results observed using both methods are complementary, and explain any unexpected results obtained from one method by using the other method.

What are the types of sampling designs in research methodology?

Sampling 4 is an important part of a research methodology and involves selecting a representative sample of the population to conduct the study, making statistical inferences about them, and estimating the characteristics of the whole population based on these inferences. There are two types of sampling designs in research methodology—probability and nonprobability.

• Probability sampling

In this type of sampling design, a sample is chosen from a larger population using some form of random selection, that is, every member of the population has an equal chance of being selected. The different types of probability sampling are:

• Systematic —sample members are chosen at regular intervals. It requires selecting a starting point for the sample and sample size determination that can be repeated at regular intervals. This type of sampling method has a predefined range; hence, it is the least time consuming.
• Stratified —researchers divide the population into smaller groups that don’t overlap but represent the entire population. While sampling, these groups can be organized, and then a sample can be drawn from each group separately.
• Cluster —the population is divided into clusters based on demographic parameters like age, sex, location, etc.
• Convenience —selects participants who are most easily accessible to researchers due to geographical proximity, availability at a particular time, etc.
• Purposive —participants are selected at the researcher’s discretion. Researchers consider the purpose of the study and the understanding of the target audience.
• Snowball —already selected participants use their social networks to refer the researcher to other potential participants.
• Quota —while designing the study, the researchers decide how many people with which characteristics to include as participants. The characteristics help in choosing people most likely to provide insights into the subject.

What are data collection methods?

During research, data are collected using various methods depending on the research methodology being followed and the research methods being undertaken. Both qualitative and quantitative research have different data collection methods, as listed below.

Qualitative research 5

• One-on-one interviews: Helps the interviewers understand a respondent’s subjective opinion and experience pertaining to a specific topic or event
• Document study/literature review/record keeping: Researchers’ review of already existing written materials such as archives, annual reports, research articles, guidelines, policy documents, etc.
• Focus groups: Constructive discussions that usually include a small sample of about 6-10 people and a moderator, to understand the participants’ opinion on a given topic.
• Qualitative observation : Researchers collect data using their five senses (sight, smell, touch, taste, and hearing).

Quantitative research 6

• Sampling: The most common type is probability sampling.
• Interviews: Commonly telephonic or done in-person.
• Observations: Structured observations are most commonly used in quantitative research. In this method, researchers make observations about specific behaviors of individuals in a structured setting.
• Document review: Reviewing existing research or documents to collect evidence for supporting the research.
• Surveys and questionnaires. Surveys can be administered both online and offline depending on the requirement and sample size.

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What are data analysis methods.

The data collected using the various methods for qualitative and quantitative research need to be analyzed to generate meaningful conclusions. These data analysis methods 7 also differ between quantitative and qualitative research.

Quantitative research involves a deductive method for data analysis where hypotheses are developed at the beginning of the research and precise measurement is required. The methods include statistical analysis applications to analyze numerical data and are grouped into two categories—descriptive and inferential.

Descriptive analysis is used to describe the basic features of different types of data to present it in a way that ensures the patterns become meaningful. The different types of descriptive analysis methods are:

• Measures of frequency (count, percent, frequency)
• Measures of central tendency (mean, median, mode)
• Measures of dispersion or variation (range, variance, standard deviation)
• Measure of position (percentile ranks, quartile ranks)

Inferential analysis is used to make predictions about a larger population based on the analysis of the data collected from a smaller population. This analysis is used to study the relationships between different variables. Some commonly used inferential data analysis methods are:

• Correlation: To understand the relationship between two or more variables.
• Cross-tabulation: Analyze the relationship between multiple variables.
• Regression analysis: Study the impact of independent variables on the dependent variable.
• Frequency tables: To understand the frequency of data.
• Analysis of variance: To test the degree to which two or more variables differ in an experiment.

Qualitative research involves an inductive method for data analysis where hypotheses are developed after data collection. The methods include:

• Content analysis: For analyzing documented information from text and images by determining the presence of certain words or concepts in texts.
• Narrative analysis: For analyzing content obtained from sources such as interviews, field observations, and surveys. The stories and opinions shared by people are used to answer research questions.
• Discourse analysis: For analyzing interactions with people considering the social context, that is, the lifestyle and environment, under which the interaction occurs.
• Grounded theory: Involves hypothesis creation by data collection and analysis to explain why a phenomenon occurred.
• Thematic analysis: To identify important themes or patterns in data and use these to address an issue.

How to choose a research methodology?

Here are some important factors to consider when choosing a research methodology: 8

• Research objectives, aims, and questions —these would help structure the research design.
• Review existing literature to identify any gaps in knowledge.
• Check the statistical requirements —if data-driven or statistical results are needed then quantitative research is the best. If the research questions can be answered based on people’s opinions and perceptions, then qualitative research is most suitable.
• Sample size —sample size can often determine the feasibility of a research methodology. For a large sample, less effort- and time-intensive methods are appropriate.
• Constraints —constraints of time, geography, and resources can help define the appropriate methodology.

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How to write a research methodology .

A research methodology should include the following components: 3,9

• Research design —should be selected based on the research question and the data required. Common research designs include experimental, quasi-experimental, correlational, descriptive, and exploratory.
• Research method —this can be quantitative, qualitative, or mixed-method.
• Reason for selecting a specific methodology —explain why this methodology is the most suitable to answer your research problem.
• Research instruments —explain the research instruments you plan to use, mainly referring to the data collection methods such as interviews, surveys, etc. Here as well, a reason should be mentioned for selecting the particular instrument.
• Sampling —this involves selecting a representative subset of the population being studied.
• Data collection —involves gathering data using several data collection methods, such as surveys, interviews, etc.
• Data analysis —describe the data analysis methods you will use once you’ve collected the data.
• Research limitations —mention any limitations you foresee while conducting your research.
• Validity and reliability —validity helps identify the accuracy and truthfulness of the findings; reliability refers to the consistency and stability of the results over time and across different conditions.
• Ethical considerations —research should be conducted ethically. The considerations include obtaining consent from participants, maintaining confidentiality, and addressing conflicts of interest.

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Frequently Asked Questions

Q1. What are the key components of research methodology?

A1. A good research methodology has the following key components:

• Research design
• Data collection procedures
• Data analysis methods
• Ethical considerations

Q2. Why is ethical consideration important in research methodology?

A2. Ethical consideration is important in research methodology to ensure the readers of the reliability and validity of the study. Researchers must clearly mention the ethical norms and standards followed during the conduct of the research and also mention if the research has been cleared by any institutional board. The following 10 points are the important principles related to ethical considerations: 10

• Participants should not be subjected to harm.
• Respect for the dignity of participants should be prioritized.
• Full consent should be obtained from participants before the study.
• Participants’ privacy should be ensured.
• Confidentiality of the research data should be ensured.
• Anonymity of individuals and organizations participating in the research should be maintained.
• The aims and objectives of the research should not be exaggerated.
• Affiliations, sources of funding, and any possible conflicts of interest should be declared.
• Communication in relation to the research should be honest and transparent.
• Misleading information and biased representation of primary data findings should be avoided.

Q3. What is the difference between methodology and method?

A3. Research methodology is different from a research method, although both terms are often confused. Research methods are the tools used to gather data, while the research methodology provides a framework for how research is planned, conducted, and analyzed. The latter guides researchers in making decisions about the most appropriate methods for their research. Research methods refer to the specific techniques, procedures, and tools used by researchers to collect, analyze, and interpret data, for instance surveys, questionnaires, interviews, etc.

Research methodology is, thus, an integral part of a research study. It helps ensure that you stay on track to meet your research objectives and answer your research questions using the most appropriate data collection and analysis tools based on your research design.

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• Research methodologies. Pfeiffer Library website. Accessed August 15, 2023. https://library.tiffin.edu/researchmethodologies/whatareresearchmethodologies
• Types of research methodology. Eduvoice website. Accessed August 16, 2023. https://eduvoice.in/types-research-methodology/
• The basics of research methodology: A key to quality research. Voxco. Accessed August 16, 2023. https://www.voxco.com/blog/what-is-research-methodology/
• Sampling methods: Types with examples. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/types-of-sampling-for-social-research/
• What is qualitative research? Methods, types, approaches, examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-qualitative-research-methods-types-examples/
• What is quantitative research? Definition, methods, types, and examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-quantitative-research-types-and-examples/
• Data analysis in research: Types & methods. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/data-analysis-in-research/#Data_analysis_in_qualitative_research
• Factors to consider while choosing the right research methodology. PhD Monster website. Accessed August 17, 2023. https://www.phdmonster.com/factors-to-consider-while-choosing-the-right-research-methodology/
• What is research methodology? Research and writing guides. Accessed August 14, 2023. https://paperpile.com/g/what-is-research-methodology/
• Ethical considerations. Business research methodology website. Accessed August 17, 2023. https://research-methodology.net/research-methodology/ethical-considerations/

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• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

• 6. The Methodology
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

The methods section describes actions taken to investigate a research problem and the rationale for the application of specific procedures or techniques used to identify, select, process, and analyze information applied to understanding the problem, thereby, allowing the reader to critically evaluate a study’s overall validity and reliability. The methodology section of a research paper answers two main questions: How was the data collected or generated? And, how was it analyzed? The writing should be direct and precise and always written in the past tense.

Kallet, Richard H. "How to Write the Methods Section of a Research Paper." Respiratory Care 49 (October 2004): 1229-1232.

Importance of a Good Methodology Section

You must explain how you obtained and analyzed your results for the following reasons:

• Readers need to know how the data was obtained because the method you chose affects the results and, by extension, how you interpreted their significance in the discussion section of your paper.
• Methodology is crucial for any branch of scholarship because an unreliable method produces unreliable results and, as a consequence, undermines the value of your analysis of the findings.
• In most cases, there are a variety of different methods you can choose to investigate a research problem. The methodology section of your paper should clearly articulate the reasons why you have chosen a particular procedure or technique.
• The reader wants to know that the data was collected or generated in a way that is consistent with accepted practice in the field of study. For example, if you are using a multiple choice questionnaire, readers need to know that it offered your respondents a reasonable range of answers to choose from.
• The method must be appropriate to fulfilling the overall aims of the study. For example, you need to ensure that you have a large enough sample size to be able to generalize and make recommendations based upon the findings.
• The methodology should discuss the problems that were anticipated and the steps you took to prevent them from occurring. For any problems that do arise, you must describe the ways in which they were minimized or why these problems do not impact in any meaningful way your interpretation of the findings.
• In the social and behavioral sciences, it is important to always provide sufficient information to allow other researchers to adopt or replicate your methodology. This information is particularly important when a new method has been developed or an innovative use of an existing method is utilized.

Bem, Daryl J. Writing the Empirical Journal Article. Psychology Writing Center. University of Washington; Denscombe, Martyn. The Good Research Guide: For Small-Scale Social Research Projects . 5th edition. Buckingham, UK: Open University Press, 2014; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008.

Structure and Writing Style

I.  Groups of Research Methods

There are two main groups of research methods in the social sciences:

• The e mpirical-analytical group approaches the study of social sciences in a similar manner that researchers study the natural sciences . This type of research focuses on objective knowledge, research questions that can be answered yes or no, and operational definitions of variables to be measured. The empirical-analytical group employs deductive reasoning that uses existing theory as a foundation for formulating hypotheses that need to be tested. This approach is focused on explanation.
• The i nterpretative group of methods is focused on understanding phenomenon in a comprehensive, holistic way . Interpretive methods focus on analytically disclosing the meaning-making practices of human subjects [the why, how, or by what means people do what they do], while showing how those practices arrange so that it can be used to generate observable outcomes. Interpretive methods allow you to recognize your connection to the phenomena under investigation. However, the interpretative group requires careful examination of variables because it focuses more on subjective knowledge.

II.  Content

The introduction to your methodology section should begin by restating the research problem and underlying assumptions underpinning your study. This is followed by situating the methods you used to gather, analyze, and process information within the overall “tradition” of your field of study and within the particular research design you have chosen to study the problem. If the method you choose lies outside of the tradition of your field [i.e., your review of the literature demonstrates that the method is not commonly used], provide a justification for how your choice of methods specifically addresses the research problem in ways that have not been utilized in prior studies.

The remainder of your methodology section should describe the following:

• Decisions made in selecting the data you have analyzed or, in the case of qualitative research, the subjects and research setting you have examined,
• Tools and methods used to identify and collect information, and how you identified relevant variables,
• The ways in which you processed the data and the procedures you used to analyze that data, and
• The specific research tools or strategies that you utilized to study the underlying hypothesis and research questions.

In addition, an effectively written methodology section should:

• Introduce the overall methodological approach for investigating your research problem . Is your study qualitative or quantitative or a combination of both (mixed method)? Are you going to take a special approach, such as action research, or a more neutral stance?
• Indicate how the approach fits the overall research design . Your methods for gathering data should have a clear connection to your research problem. In other words, make sure that your methods will actually address the problem. One of the most common deficiencies found in research papers is that the proposed methodology is not suitable to achieving the stated objective of your paper.
• Describe the specific methods of data collection you are going to use , such as, surveys, interviews, questionnaires, observation, archival research. If you are analyzing existing data, such as a data set or archival documents, describe how it was originally created or gathered and by whom. Also be sure to explain how older data is still relevant to investigating the current research problem.
• Explain how you intend to analyze your results . Will you use statistical analysis? Will you use specific theoretical perspectives to help you analyze a text or explain observed behaviors? Describe how you plan to obtain an accurate assessment of relationships, patterns, trends, distributions, and possible contradictions found in the data.
• Provide background and a rationale for methodologies that are unfamiliar for your readers . Very often in the social sciences, research problems and the methods for investigating them require more explanation/rationale than widely accepted rules governing the natural and physical sciences. Be clear and concise in your explanation.
• Provide a justification for subject selection and sampling procedure . For instance, if you propose to conduct interviews, how do you intend to select the sample population? If you are analyzing texts, which texts have you chosen, and why? If you are using statistics, why is this set of data being used? If other data sources exist, explain why the data you chose is most appropriate to addressing the research problem.
• Provide a justification for case study selection . A common method of analyzing research problems in the social sciences is to analyze specific cases. These can be a person, place, event, phenomenon, or other type of subject of analysis that are either examined as a singular topic of in-depth investigation or multiple topics of investigation studied for the purpose of comparing or contrasting findings. In either method, you should explain why a case or cases were chosen and how they specifically relate to the research problem.
• Describe potential limitations . Are there any practical limitations that could affect your data collection? How will you attempt to control for potential confounding variables and errors? If your methodology may lead to problems you can anticipate, state this openly and show why pursuing this methodology outweighs the risk of these problems cropping up.

NOTE:   Once you have written all of the elements of the methods section, subsequent revisions should focus on how to present those elements as clearly and as logically as possibly. The description of how you prepared to study the research problem, how you gathered the data, and the protocol for analyzing the data should be organized chronologically. For clarity, when a large amount of detail must be presented, information should be presented in sub-sections according to topic. If necessary, consider using appendices for raw data.

ANOTHER NOTE: If you are conducting a qualitative analysis of a research problem , the methodology section generally requires a more elaborate description of the methods used as well as an explanation of the processes applied to gathering and analyzing of data than is generally required for studies using quantitative methods. Because you are the primary instrument for generating the data [e.g., through interviews or observations], the process for collecting that data has a significantly greater impact on producing the findings. Therefore, qualitative research requires a more detailed description of the methods used.

YET ANOTHER NOTE:   If your study involves interviews, observations, or other qualitative techniques involving human subjects , you may be required to obtain approval from the university's Office for the Protection of Research Subjects before beginning your research. This is not a common procedure for most undergraduate level student research assignments. However, i f your professor states you need approval, you must include a statement in your methods section that you received official endorsement and adequate informed consent from the office and that there was a clear assessment and minimization of risks to participants and to the university. This statement informs the reader that your study was conducted in an ethical and responsible manner. In some cases, the approval notice is included as an appendix to your paper.

III.  Problems to Avoid

Irrelevant Detail The methodology section of your paper should be thorough but concise. Do not provide any background information that does not directly help the reader understand why a particular method was chosen, how the data was gathered or obtained, and how the data was analyzed in relation to the research problem [note: analyzed, not interpreted! Save how you interpreted the findings for the discussion section]. With this in mind, the page length of your methods section will generally be less than any other section of your paper except the conclusion.

Unnecessary Explanation of Basic Procedures Remember that you are not writing a how-to guide about a particular method. You should make the assumption that readers possess a basic understanding of how to investigate the research problem on their own and, therefore, you do not have to go into great detail about specific methodological procedures. The focus should be on how you applied a method , not on the mechanics of doing a method. An exception to this rule is if you select an unconventional methodological approach; if this is the case, be sure to explain why this approach was chosen and how it enhances the overall process of discovery.

Problem Blindness It is almost a given that you will encounter problems when collecting or generating your data, or, gaps will exist in existing data or archival materials. Do not ignore these problems or pretend they did not occur. Often, documenting how you overcame obstacles can form an interesting part of the methodology. It demonstrates to the reader that you can provide a cogent rationale for the decisions you made to minimize the impact of any problems that arose.

Literature Review Just as the literature review section of your paper provides an overview of sources you have examined while researching a particular topic, the methodology section should cite any sources that informed your choice and application of a particular method [i.e., the choice of a survey should include any citations to the works you used to help construct the survey].

It’s More than Sources of Information! A description of a research study's method should not be confused with a description of the sources of information. Such a list of sources is useful in and of itself, especially if it is accompanied by an explanation about the selection and use of the sources. The description of the project's methodology complements a list of sources in that it sets forth the organization and interpretation of information emanating from those sources.

Azevedo, L.F. et al. "How to Write a Scientific Paper: Writing the Methods Section." Revista Portuguesa de Pneumologia 17 (2011): 232-238; Blair Lorrie. “Choosing a Methodology.” In Writing a Graduate Thesis or Dissertation , Teaching Writing Series. (Rotterdam: Sense Publishers 2016), pp. 49-72; Butin, Dan W. The Education Dissertation A Guide for Practitioner Scholars . Thousand Oaks, CA: Corwin, 2010; Carter, Susan. Structuring Your Research Thesis . New York: Palgrave Macmillan, 2012; Kallet, Richard H. “How to Write the Methods Section of a Research Paper.” Respiratory Care 49 (October 2004):1229-1232; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008. Methods Section. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Rudestam, Kjell Erik and Rae R. Newton. “The Method Chapter: Describing Your Research Plan.” In Surviving Your Dissertation: A Comprehensive Guide to Content and Process . (Thousand Oaks, Sage Publications, 2015), pp. 87-115; What is Interpretive Research. Institute of Public and International Affairs, University of Utah; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University; Methods and Materials. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College.

Writing Tip

Statistical Designs and Tests? Do Not Fear Them!

Don't avoid using a quantitative approach to analyzing your research problem just because you fear the idea of applying statistical designs and tests. A qualitative approach, such as conducting interviews or content analysis of archival texts, can yield exciting new insights about a research problem, but it should not be undertaken simply because you have a disdain for running a simple regression. A well designed quantitative research study can often be accomplished in very clear and direct ways, whereas, a similar study of a qualitative nature usually requires considerable time to analyze large volumes of data and a tremendous burden to create new paths for analysis where previously no path associated with your research problem had existed.

To locate data and statistics, GO HERE .

Another Writing Tip

Knowing the Relationship Between Theories and Methods

There can be multiple meaning associated with the term "theories" and the term "methods" in social sciences research. A helpful way to delineate between them is to understand "theories" as representing different ways of characterizing the social world when you research it and "methods" as representing different ways of generating and analyzing data about that social world. Framed in this way, all empirical social sciences research involves theories and methods, whether they are stated explicitly or not. However, while theories and methods are often related, it is important that, as a researcher, you deliberately separate them in order to avoid your theories playing a disproportionate role in shaping what outcomes your chosen methods produce.

Introspectively engage in an ongoing dialectic between the application of theories and methods to help enable you to use the outcomes from your methods to interrogate and develop new theories, or ways of framing conceptually the research problem. This is how scholarship grows and branches out into new intellectual territory.

Reynolds, R. Larry. Ways of Knowing. Alternative Microeconomics . Part 1, Chapter 3. Boise State University; The Theory-Method Relationship. S-Cool Revision. United Kingdom.

Yet Another Writing Tip

Methods and the Methodology

Do not confuse the terms "methods" and "methodology." As Schneider notes, a method refers to the technical steps taken to do research . Descriptions of methods usually include defining and stating why you have chosen specific techniques to investigate a research problem, followed by an outline of the procedures you used to systematically select, gather, and process the data [remember to always save the interpretation of data for the discussion section of your paper].

The methodology refers to a discussion of the underlying reasoning why particular methods were used . This discussion includes describing the theoretical concepts that inform the choice of methods to be applied, placing the choice of methods within the more general nature of academic work, and reviewing its relevance to examining the research problem. The methodology section also includes a thorough review of the methods other scholars have used to study the topic.

Bryman, Alan. "Of Methods and Methodology." Qualitative Research in Organizations and Management: An International Journal 3 (2008): 159-168; Schneider, Florian. “What's in a Methodology: The Difference between Method, Methodology, and Theory…and How to Get the Balance Right?” PoliticsEastAsia.com. Chinese Department, University of Leiden, Netherlands.

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What is UX Research: The Ultimate Guide for UX Researchers

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The UX researcher’s toolkit: 11 UX research methods and when to use them

After defining your objectives and planning your research framework, it’s time to choose the research technique that will best serve your project's goals and yield the right insights. While user research is often treated as an afterthought, it should inform every design decision. In this chapter, we walk you through the most common research methods and help you choose the right one for you.

What are UX research methods?

A UX research method is a way of generating insights about your users, their behavior, motivations, and needs.

These methods help:

• Learn about user behavior and attitudes
• Identify key pain points and challenges in the user interface
• Develop user personas to identify user needs and drive solutions
• Test user interface designs to see what works and what doesn’t

You can use research methodologies like user interviews, surveys, focus groups, card sorting, usability testing to identify user challenges and turn them into opportunities to improve the user experience.

More of a visual learner? Check out this video for a speedy rundown. If you’re ready to get stuck in, jump straight to our full breakdown .

The most common types of user research

First, let’s talk about the types of UX research. Every individual research method falls under these types, which reflect different goals and objectives for conducting research.

Here’s a quick overview:

Qualitative vs. quantitative

All research methods are either quantitative or qualitative . Qualitative research focuses on capturing subjective insights into users' experiences. It aims to understand the underlying reasons, motivations, and behaviors of individuals.

Quantitative research, on the other hand, involves collecting and analyzing numerical data to identify patterns, trends, and significance. It aims to quantify user behaviors, preferences, and attitudes, allowing for generalizations and statistical insights.

Qualitative research also typically involves a smaller sample size than quantitative research. Nielsen Norman Group recommends 40 participants—see our full rundown of how many user testers you need for different research methods .

Attitudinal vs. behavioral

Attitudinal research is about understanding users' attitudes, perceptions, and beliefs. It delves into the 'why' behind user decisions and actions. It often involves surveys or interviews where users are asked about their feelings, preferences, or perceptions towards a product or service. It's subjective in nature, aiming to capture people's emotions and opinions.

Behavioral research is about what users do rather than what they say they do or would do. This kind of research is often based on observation methods like usability testing, eye-tracking, or heat maps to understand user behavior.

Generative vs. evaluative

Generative research is all about generating new ideas, concepts, and insights to fuel the design process. You might run brainstorming sessions with groups of users, card sorting, and co-design sessions to inspire creativity and guide the development of user-centered solutions.

On the other hand, evaluative research focuses on assessing the usability, effectiveness, and overall quality of existing designs or prototypes. Once you’ve developed a prototype of your product, it's time to evaluate its strengths and weaknesses. You can compare different versions of a product design or feature through A/B testing—ensuring your UX design meets user needs and expectations.

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11 Best UX research methods and when to use them

There are various UX research techniques—each method serves a specific purpose and can provide unique insights into user behaviors and preferences. In this section, we’ll highlight the most common research techniques you need to know.

Read on for an at-a-glance table, and full breakdown of each method.

1. User interviews

Tl;dr: user interviews.

Directly ask users about their experiences with a product to understand their thoughts, feelings, and problems

✅ Provides detailed insights that survey may miss ❌ May not represent the wider user base; depends on user’s memory and honesty

User interviews are a qualitative research method that involves having open-ended and guided discussions with users to gather in-depth insights about their experiences, needs, motivations, and behaviors.

Typically, you would ask a few questions on a specific topic during a user interview and analyze participants' answers. The results you get will depend on how well you form and ask questions, as well as follow up on participants’ answers.

“As a researcher, it's our responsibility to drive the user to their actual problems,” says Yuliya Martinavichene , User Experience Researcher at Zinio. She adds, “The narration of incidents can help you analyze a lot of hidden details with regard to user behavior.”

That’s why you should:

• Start with a wide context : Make sure that your questions don’t start with your product
• Ask questions: Always ask questions that focus on the tasks that users are trying to complete
• Invest in analysis : Get transcripts done and share the findings with your team

Tanya Nativ , Design Researcher at Sketch recommends defining the goals and assumptions internally. “Our beliefs about our users’ behavior really help to structure good questions and get to the root of the problem and its solution,” she explains.

It's easy to be misunderstood if you don't have experience writing interview questions. You can get someone to review them for you or use our Question Bank of 350+ research questions .

When to conduct user interviews

This method is typically used at the start and end of your project. At the start of a project, you can establish a strong understanding of your target users, their perspectives, and the context in which they’ll interact with your product. By the end of your project, new user interviews—often with a different set of individuals—offer a litmus test for your product's usability and appeal, providing firsthand accounts of experiences, perceived strengths, and potential areas for refinement.

2. Field studies

Tl;dr: field studies.

Observe users in their natural environment to inform design decisions with real-world context

✅ Provides contextual insights into user behavior in real-world situations ✅ Helps identify external factors and conditions that influence user experience ❌ Can be time-consuming and resource-intensive to conduct ❌ Participants may behave differently when they know they are being observed (Hawthorne effect)

Field studies—also known as ethnographic research—are research activities that take place in the user’s environment rather than in your lab or office. They’re a great method for uncovering context, unknown motivations, or constraints that affect the user experience.

An advantage of field studies is observing people in their natural environment, giving you a glimpse at the context in which your product is used. It’s useful to understand the context in which users complete tasks, learn about their needs, and collect in-depth user stories.

When to conduct field studies

This method can be used at all stages of your project—two key times you may want to conduct field studies are:

• As part of the discovery and exploration stage to define direction and understand the context around when and how users interact with the product
• During usability testing, once you have a prototype, to evaluate the effectiveness of the solution or validate design assumptions in real-world contexts

3. Focus groups

Tl;dr: focus groups.

Gather qualitative data from a group of users discussing their experiences and opinions about a product

✅ Allows for diverse perspectives to be shared and discussed ❌ Group dynamics may influence individual opinions

A focus group is a qualitative research method that includes the study of a group of people, their beliefs, and opinions. It’s typically used for market research or gathering feedback on products and messaging.

Focus groups can help you better grasp:

• How users perceive your product
• What users believe are a product’s most important features
• What problems do users experience with the product

As with any qualitative research method, the quality of the data collected through focus groups is only as robust as the preparation. So, it’s important to prepare a UX research plan you can refer to during the discussion.

Here’s some things to consider:

• Write a script to guide the conversation
• Ask clear, open-ended questions focused on the topics you’re trying to learn about
• Include around five to ten participants to keep the sessions focused and organized

When to conduct focus groups

It’s easier to use this research technique when you're still formulating your concept, product, or service—to explore user preferences, gather initial reactions, and generate ideas. This is because, in the early stages, you have flexibility and can make significant changes without incurring high costs.

Another way some researchers employ focus groups is post-launch to gather feedback and identify potential improvements. However, you can also use other methods here which may be more effective for identifying usability issues. For example, a platform like Maze can provide detailed, actionable data about how users interact with your product. These quantitative results are a great accompaniment to the qualitative data gathered from your focus group.

4. Diary studies

Tl;dr: diary studies.

Get deep insights into user thoughts and feelings by having them keep a product-related diary over a set period of time, typically a couple of weeks

✅ Gives you a peak into how users interact with your product in their day-to-day ❌ Depends on how motivated and dedicated the users are

Diary studies involve asking users to track their usage and thoughts on your product by keeping logs or diaries, taking photos, explaining their activities, and highlighting things that stood out to them.

“Diary studies are one of the few ways you can get a peek into how users interact with our product in a real-world scenario,” says Tanya.

A diary study helps you tell the story of how products and services fit into people’s daily lives, and the touch-points and channels they choose to complete their tasks.

There’s several key questions to consider before conducting diary research, from what kind of diary you want—freeform or structured, and digital or paper—to how often you want participants to log their thoughts.

• Open, ‘freeform’ diary: Users have more freedom to record what and when they like, but can also lead to missed opportunities to capture data users might overlook
• Closed, ‘structured; diary: Users follow a stricter entry-logging process and answer pre-set questions

Remember to determine the trigger: a signal that lets the participants know when they should log their feedback. Tanya breaks these triggers down into the following:

• Interval-contingent trigger : Participants fill out the diary at specific intervals such as one entry per day, or one entry per week
• Signal-contingent trigger : You tell the participant when to make an entry and how you would prefer them to communicate it to you as well as your preferred type of communication
• Event-contingent trigger : The participant makes an entry whenever a defined event occurs

When to conduct diary studies

Diary studies are often valuable when you need to deeply understand users' behaviors, routines, and pain points in real-life contexts. This could be when you're:

• Conceptualizing a new product or feature: Gain insights into user habits, needs, and frustrations to inspire your design
• Trying to enhance an existing product: Identify areas where users are having difficulties or where there are opportunities for better user engagement

TL;DR: Surveys

Collect quantitative data from a large sample of users about their experiences, preferences, and satisfaction with a product

✅ Provides a broad overview of user opinions and trends ❌ May lack in-depth insights and context behind user responses

Although surveys are primarily used for quantitative research, they can also provided qualitative data, depending on whether you use closed or open-ended questions:

• Closed-ended questions come with a predefined set of answers to choose from using formats like rating scales, rankings, or multiple choice. This results in quantitative data.
• Open-ended question s are typically open-text questions where test participants give their responses in a free-form style. This results in qualitative data.

Matthieu Dixte , Product Researcher at Maze, explains the benefit of surveys: “With open-ended questions, researchers get insight into respondents' opinions, experiences, and explanations in their own words. This helps explore nuances that quantitative data alone may not capture.”

So, how do you make sure you’re asking the right survey questions? Gregg Bernstein , UX Researcher at Signal, says that when planning online surveys, it’s best to avoid questions that begin with “How likely are you to…?” Instead, Gregg says asking questions that start with “Have you ever… ?” will prompt users to give more specific and measurable answers.

Make sure your questions:

• Are easy to understand
• Don't guide participants towards a particular answer
• Include both closed-ended and open-ended questions
• Respect users and their privacy
• Are consistent in terms of format

To learn more about survey design, check out this guide .

When to conduct surveys

While surveys can be used at all stages of project development, and are ideal for continuous product discovery , the specific timing and purpose may vary depending on the research goals. For example, you can run surveys at:

• Conceptualization phase to gather preliminary data, and identify patterns, trends, or potential user segments
• Post-launch or during iterative design cycles to gather feedback on user satisfaction, feature usage, or suggestions for improvements

6. Card sorting

Tl;dr: card sorting.

Understand how users categorize and prioritize information within a product or service to structure your information in line with user expectations

✅ Helps create intuitive information architecture and navigation ❌ May not accurately reflect real-world user behavior and decision-making

Card sorting is an important step in creating an intuitive information architecture (IA) and user experience. It’s also a great technique to generate ideas, naming conventions, or simply see how users understand topics.

In this UX research method, participants are presented with cards featuring different topics or information, and tasked with grouping the cards into categories that make sense to them.

There are three types of card sorting:

• Open card sorting: Participants organize topics into categories that make sense to them and name those categories, thus generating new ideas and names
• Hybrid card sorting: Participants can sort cards into predefined categories, but also have the option to create their own categories
• Closed card sorting: Participants are given predefined categories and asked to sort the items into the available groups

Card sorting type comparison table

You can run a card sorting session using physical index cards or digitally with a UX research tool like Maze to simulate the drag-and-drop activity of dividing cards into groups. Running digital card sorting is ideal for any type of card sort, and moderated or unmoderated sessions .

Read more about card sorting and learn how to run a card sorting session here .

When to conduct card sorting

Card sorting isn’t limited to a single stage of design or development—it can be employed anytime you need to explore how users categorize or perceive information. For example, you may want to use card sorting if you need to:

• Understand how users perceive ideas
• Evaluate and prioritize potential solutions
• Generate name ideas and understand naming conventions
• Learn how users expect navigation to work
• Decide how to group content on a new or existing site
• Restructure information architecture

7. Tree testing

Tl;dr: tree testing.

Evaluate the findability of existing information within a product's hierarchical structure or navigation

✅ Identifies potential issues in the information architecture ❌ Focuses on navigation structure, not visual design or content

During tree testing a text-only version of the site is given to your participants, who are asked to complete a series of tasks requiring them to locate items on the app or website.

The data collected from a tree test helps you understand where users intuitively navigate first, and is an effective way to assess the findability, labeling, and information architecture of a product.

We recommend keeping these sessions short, ranging from 15 to 20 minutes, and asking participants to complete no more than ten tasks. This helps ensure participants remain focused and engaged, leading to more reliable and accurate data, and avoiding fatigue.

If you’re using a platform like Maze to run remote testing, you can easily recruit participants based on various demographic filters, including industry and country. This way, you can uncover a broader range of user preferences, ensuring a more comprehensive understanding of your target audience.

To learn more about tree testing, check out this chapter .

When to conduct tree testing

Tree testing is often done at an early stage in the design or redesign process. That’s because it’s more cost-effective to address errors at the start of a project—rather than making changes later in the development process or after launch.

However, it can be helpful to employ tree testing as a method when adding new features, particularly alongside card sorting.

While tree testing and card sorting can both help you with categorizing the content on a website, it’s important to note that they each approach this from a different angle and are used at different stages during the research process. Ideally, you should use the two in tandem: card sorting is recommended when defining and testing a new website architecture, while tree testing is meant to help you test how the navigation performs with users.

8. Usability testing

Tl;dr: usability testing.

Observe users completing specific tasks with a product to identify usability issues and potential improvements

✅ Provides direct insights into user behavior and reveals pain points ❌ Conducted in a controlled environment, may not fully represent real-world usage

Usability testing evaluates your product with people by getting them to complete tasks while you observe and note their interactions (either during or after the test). The goal of conducting usability testing is to understand if your design is intuitive and easy to use. A sign of success is if users can easily accomplish their goals and complete tasks with your product.

There are various usability testing methods that you can use, such as moderated vs. unmoderated or qualitative vs. quantitative —and selecting the right one depends on your research goals, resources, and timeline.

Usability testing is usually performed with functional mid or hi-fi prototypes . If you have a Figma, InVision, Sketch, or prototype ready, you can import it into a platform like Maze and start testing your design with users immediately.

The tasks you create for usability tests should be:

• Realistic, and describe a scenario
• Actionable, and use action verbs (create, sign up, buy, etc)

Be mindful of using leading words such as ‘click here’ or ‘go to that page’ in your tasks. These instructions bias the results by helping users complete their tasks—something that doesn’t happen in real life.

✨ Product tip

With Maze, you can test your prototype and live website with real users to filter out cognitive biases, and gather actionable insights that fuel product decisions.

When to conduct usability testing

To inform your design decisions, you should do usability testing early and often in the process . Here are some guidelines to help you decide when to do usability testing:

• Before you start designing
• Once you have a wireframe or prototype
• Prior to the launch of the product
• At regular intervals after launch

To learn more about usability testing, check out our complete guide to usability testing .

9. Five-second testing

Tl;dr: five-second testing.

Gauge users' first impressions and understanding of a design or layout

✅ Provides insights into the instant clarity and effectiveness of visual communication ❌ Limited to first impressions, does not assess full user experience or interaction

In five-second testing , participants are (unsurprisingly) given five seconds to view an image like a design or web page, and then they’re asked questions about the design to gauge their first impressions.

Why five seconds? According to data , 55% of visitors spend less than 15 seconds on a website, so it;s essential to grab someone’s attention in the first few seconds of their visit. With a five-second test, you can quickly determine what information users perceive and their impressions during the first five seconds of viewing a design.

Product tip 💡

And if you’re using Maze, you can simply upload an image of the screen you want to test, or browse your prototype and select a screen. Plus, you can star individual comments and automatically add them to your report to share with stakeholders.

When to conduct five-second testing

Five-second testing is typically conducted in the early stages of the design process, specifically during initial concept testing or prototype development. This way, you can evaluate your design's initial impact and make early refinements or adjustments to ensure its effectiveness, before putting design to development.

To learn more, check out our chapter on five-second testing .

10. A/B testing

Tl;dr: a/b testing.

Compare two versions of a design or feature to determine which performs better based on user engagement

✅ Provides data-driven insights to guide design decisions and optimize user experience ❌ Requires a large sample size and may not account for long-term effects or complex interactions

A/B testing , also known as split testing, compares two or more versions of a webpage, interface, or feature to determine which performs better regarding engagement, conversions, or other predefined metrics.

It involves randomly dividing users into different groups and giving each group a different version of the design element being tested. For example, let's say the primary call-to-action on the page is a button that says ‘buy now’.

You're considering making changes to its design to see if it can lead to higher conversions, so you create two versions:

• Version A : The original design with the ‘buy now’ button positioned below the product description—shown to group A
• Version B : A variation with the ‘buy now’ button now prominently displayed above the product description—shown to group B

Over a planned period, you measure metrics like click-through rates, add-to-cart rates, and actual purchases to assess the performance of each variation. You find that Group B had significantly higher click-through and conversion rates than Group A. This indicates that showing the button above the product description drove higher user engagement and conversions.

Check out our A/B testing guide for more in-depth examples and guidance on how to run these tests.

When to conduct A/B testing

A/B testing can be used at all stages of the design and development process—whenever you want to collect direct, quantitative data and confirm a suspicion, or settle a design debate. This iterative testing approach allows you to continually improve your website's performance and user experience based on data-driven insights.

11. Concept testing

Tl;dr: concept testing.

Evaluate users' reception and understanding of a new product, feature, or design idea before moving on to development

✅ Helps validate and refine concepts based on user feedback ❌ Relies on users' perception and imagination, may not reflect actual use

Concept testing is a type of research that evaluates the feasibility, appeal, and potential success of a new product before you build it. It centers the user in the ideation process, using UX research methods like A/B testing, surveys, and customer interviews.

There’s no one way to run a concept test—you can opt for concept testing surveys, interviews, focus groups, or any other method that gets qualitative data on your concept.

*Dive into our complete guide to concept testing for more tips and tricks on getting started. *

When to conduct concept testing

Concept testing helps gauge your audience’s interest, understanding, and likelihood-to-purchase, before committing time and resources to a concept. However, it can also be useful further down the product development line—such as when defining marketing messaging or just before launching.

Which is the best UX research type?

The best research type varies depending on your project; what your objectives are, and what stage you’re in. Ultimately, the ideal type of research is one which provides the insights required, using the available resources.

For example, if you're at the early ideation or product discovery stage, generative research methods can help you generate new ideas, understand user needs, and explore possibilities. As you move to the design and development phase, evaluative research methods and quantitative data become crucial.

Discover the UX research trends shaping the future of the industry and why the best results come from a combination of different research methods.

How to choose the right user experience research method

In an ideal world, a combination of all the insights you gain from multiple types of user research methods would guide every design decision. In practice, this can be hard to execute due to resources.

Sometimes the right methodology is the one you can get buy-in, budget, and time for.

Gregg Bernstein , UX Researcher at Signal

UX research tools can help streamline the research process, making regular testing and application of diverse methods more accessible—so you always keep the user at the center of your design process. Some other key tips to remember when choosing your method are:

Define the goals and problems

A good way to inform your choice of user experience research method is to start by considering your goals. You might want to browse UX research templates or read about examples of research.

Michael Margolis , UX Research Partner at Google Ventures, recommends answering questions like:

• “What do your users need?”
• “What are your users struggling with?”
• “How can you help your users?”

Understand the design process stage

If your team is very early in product development, generative research —like field studies—make sense. If you need to test design mockups or a prototype, evaluative research methods—such as usability testing—will work best.

This is something they’re big on at Sketch, as we heard from Design Researcher, Tanya Nativ. She says, “In the discovery phase, we focus on user interviews and contextual inquiries. The testing phase is more about dogfooding, concept testing, and usability testing. Once a feature has been launched, it’s about ongoing listening.”

Consider the type of insights required

If you're looking for rich, qualitative data that delves into user behaviors, motivations, and emotions, then methods like user interviews or field studies are ideal. They’ll help you uncover the ‘why’ behind user actions.

On the other hand, if you need to gather quantitative data to measure user satisfaction or compare different design variations, methods like surveys or A/B testing are more suitable. These methods will help you get hard numbers and concrete data on preferences and behavior.

*Discover the UX research trends shaping the future of the industry and why the best results come from a combination of different research methods. *

Build a deeper understanding of your users with UX research

Think of UX research methods as building blocks that work together to create a well-rounded understanding of your users. Each method brings its own unique strengths, whether it's human empathy from user interviews or the vast data from surveys.

But it's not just about choosing the right UX research methods; the research platform you use is equally important. You need a platform that empowers your team to collect data, analyze, and collaborate seamlessly.

Simplifying product research is simple with Maze. From tree testing to card sorting, prototype testing to user interview analysis—Maze makes getting actionable insights easy, whatever method you opt for.

Meanwhile, if you want to know more about testing methods, head on to the next chapter all about tree testing .

Get valuable insights from real users

Conduct impactful UX research with Maze and improve your product experience and customer satisfaction.

Frequently asked questions

How do you choose the right UX research method?

Choosing the right research method depends on your goals. Some key things to consider are:

• The feature/product you’re testing
• The type of data you’re looking for
• The design stage
• The time and resources you have available

What is the best UX research method?

The best research method is the one you have the time, resources, and budget for that meets your specific needs and goals. Most research tools, like Maze, will accommodate a variety of UX research and testing techniques.

When to use which user experience research method?

Selecting which user research method to use—if budget and resources aren’t a factor—depends on your goals. UX research methods provide different types of data:

• Qualitative vs quantitative
• Attitudinal vs behavioral
• Generative vs evaluative

Identify your goals, then choose a research method that gathers the user data you need.

What results can I expect from UX research?

Here are some of the key results you can expect from actioning the insights uncovered during UX research:

• Improved user satisfaction
• Increased usability
• Better product fit
• Informed design decisions
• Reduced development costs
• Higher conversion rates
• Increased customer loyalty and retention

Tree Testing: Your Guide to Improve Navigation and UX

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

2.2 Research Methods

Learning objectives.

By the end of this section, you should be able to:

• Recall the 6 Steps of the Scientific Method
• Differentiate between four kinds of research methods: surveys, field research, experiments, and secondary data analysis.
• Explain the appropriateness of specific research approaches for specific topics.

Sociologists examine the social world, see a problem or interesting pattern, and set out to study it. They use research methods to design a study. Planning the research design is a key step in any sociological study. Sociologists generally choose from widely used methods of social investigation: primary source data collection such as survey, participant observation, ethnography, case study, unobtrusive observations, experiment, and secondary data analysis , or use of existing sources. Every research method comes with plusses and minuses, and the topic of study strongly influences which method or methods are put to use. When you are conducting research think about the best way to gather or obtain knowledge about your topic, think of yourself as an architect. An architect needs a blueprint to build a house, as a sociologist your blueprint is your research design including your data collection method.

When entering a particular social environment, a researcher must be careful. There are times to remain anonymous and times to be overt. There are times to conduct interviews and times to simply observe. Some participants need to be thoroughly informed; others should not know they are being observed. A researcher wouldn’t stroll into a crime-ridden neighborhood at midnight, calling out, “Any gang members around?”

Making sociologists’ presence invisible is not always realistic for other reasons. That option is not available to a researcher studying prison behaviors, early education, or the Ku Klux Klan. Researchers can’t just stroll into prisons, kindergarten classrooms, or Klan meetings and unobtrusively observe behaviors or attract attention. In situations like these, other methods are needed. Researchers choose methods that best suit their study topics, protect research participants or subjects, and that fit with their overall approaches to research.

As a research method, a survey collects data from subjects who respond to a series of questions about behaviors and opinions, often in the form of a questionnaire or an interview. The survey is one of the most widely used scientific research methods. The standard survey format allows individuals a level of anonymity in which they can express personal ideas.

At some point, most people in the United States respond to some type of survey. The 2020 U.S. Census is an excellent example of a large-scale survey intended to gather sociological data. Since 1790, United States has conducted a survey consisting of six questions to received demographical data pertaining to residents. The questions pertain to the demographics of the residents who live in the United States. Currently, the Census is received by residents in the United Stated and five territories and consists of 12 questions.

Not all surveys are considered sociological research, however, and many surveys people commonly encounter focus on identifying marketing needs and strategies rather than testing a hypothesis or contributing to social science knowledge. Questions such as, “How many hot dogs do you eat in a month?” or “Were the staff helpful?” are not usually designed as scientific research. The Nielsen Ratings determine the popularity of television programming through scientific market research. However, polls conducted by television programs such as American Idol or So You Think You Can Dance cannot be generalized, because they are administered to an unrepresentative population, a specific show’s audience. You might receive polls through your cell phones or emails, from grocery stores, restaurants, and retail stores. They often provide you incentives for completing the survey.

Sociologists conduct surveys under controlled conditions for specific purposes. Surveys gather different types of information from people. While surveys are not great at capturing the ways people really behave in social situations, they are a great method for discovering how people feel, think, and act—or at least how they say they feel, think, and act. Surveys can track preferences for presidential candidates or reported individual behaviors (such as sleeping, driving, or texting habits) or information such as employment status, income, and education levels.

A survey targets a specific population , people who are the focus of a study, such as college athletes, international students, or teenagers living with type 1 (juvenile-onset) diabetes. Most researchers choose to survey a small sector of the population, or a sample , a manageable number of subjects who represent a larger population. The success of a study depends on how well a population is represented by the sample. In a random sample , every person in a population has the same chance of being chosen for the study. As a result, a Gallup Poll, if conducted as a nationwide random sampling, should be able to provide an accurate estimate of public opinion whether it contacts 2,000 or 10,000 people.

After selecting subjects, the researcher develops a specific plan to ask questions and record responses. It is important to inform subjects of the nature and purpose of the survey up front. If they agree to participate, researchers thank subjects and offer them a chance to see the results of the study if they are interested. The researcher presents the subjects with an instrument, which is a means of gathering the information.

A common instrument is a questionnaire. Subjects often answer a series of closed-ended questions . The researcher might ask yes-or-no or multiple-choice questions, allowing subjects to choose possible responses to each question. This kind of questionnaire collects quantitative data —data in numerical form that can be counted and statistically analyzed. Just count up the number of “yes” and “no” responses or correct answers, and chart them into percentages.

Questionnaires can also ask more complex questions with more complex answers—beyond “yes,” “no,” or checkbox options. These types of inquiries use open-ended questions that require short essay responses. Participants willing to take the time to write those answers might convey personal religious beliefs, political views, goals, or morals. The answers are subjective and vary from person to person. How do you plan to use your college education?

Some topics that investigate internal thought processes are impossible to observe directly and are difficult to discuss honestly in a public forum. People are more likely to share honest answers if they can respond to questions anonymously. This type of personal explanation is qualitative data —conveyed through words. Qualitative information is harder to organize and tabulate. The researcher will end up with a wide range of responses, some of which may be surprising. The benefit of written opinions, though, is the wealth of in-depth material that they provide.

An interview is a one-on-one conversation between the researcher and the subject, and it is a way of conducting surveys on a topic. However, participants are free to respond as they wish, without being limited by predetermined choices. In the back-and-forth conversation of an interview, a researcher can ask for clarification, spend more time on a subtopic, or ask additional questions. In an interview, a subject will ideally feel free to open up and answer questions that are often complex. There are no right or wrong answers. The subject might not even know how to answer the questions honestly.

Questions such as “How does society’s view of alcohol consumption influence your decision whether or not to take your first sip of alcohol?” or “Did you feel that the divorce of your parents would put a social stigma on your family?” involve so many factors that the answers are difficult to categorize. A researcher needs to avoid steering or prompting the subject to respond in a specific way; otherwise, the results will prove to be unreliable. The researcher will also benefit from gaining a subject’s trust, from empathizing or commiserating with a subject, and from listening without judgment.

Surveys often collect both quantitative and qualitative data. For example, a researcher interviewing people who are incarcerated might receive quantitative data, such as demographics – race, age, sex, that can be analyzed statistically. For example, the researcher might discover that 20 percent of incarcerated people are above the age of 50. The researcher might also collect qualitative data, such as why people take advantage of educational opportunities during their sentence and other explanatory information.

The survey can be carried out online, over the phone, by mail, or face-to-face. When researchers collect data outside a laboratory, library, or workplace setting, they are conducting field research, which is our next topic.

Field Research

The work of sociology rarely happens in limited, confined spaces. Rather, sociologists go out into the world. They meet subjects where they live, work, and play. Field research refers to gathering primary data from a natural environment. To conduct field research, the sociologist must be willing to step into new environments and observe, participate, or experience those worlds. In field work, the sociologists, rather than the subjects, are the ones out of their element.

The researcher interacts with or observes people and gathers data along the way. The key point in field research is that it takes place in the subject’s natural environment, whether it’s a coffee shop or tribal village, a homeless shelter or the DMV, a hospital, airport, mall, or beach resort.

While field research often begins in a specific setting , the study’s purpose is to observe specific behaviors in that setting. Field work is optimal for observing how people think and behave. It seeks to understand why they behave that way. However, researchers may struggle to narrow down cause and effect when there are so many variables floating around in a natural environment. And while field research looks for correlation, its small sample size does not allow for establishing a causal relationship between two variables. Indeed, much of the data gathered in sociology do not identify a cause and effect but a correlation .

Sociology in the Real World

Beyoncé and lady gaga as sociological subjects.

Sociologists have studied Lady Gaga and Beyoncé and their impact on music, movies, social media, fan participation, and social equality. In their studies, researchers have used several research methods including secondary analysis, participant observation, and surveys from concert participants.

In their study, Click, Lee & Holiday (2013) interviewed 45 Lady Gaga fans who utilized social media to communicate with the artist. These fans viewed Lady Gaga as a mirror of themselves and a source of inspiration. Like her, they embrace not being a part of mainstream culture. Many of Lady Gaga’s fans are members of the LGBTQ community. They see the “song “Born This Way” as a rallying cry and answer her calls for “Paws Up” with a physical expression of solidarity—outstretched arms and fingers bent and curled to resemble monster claws.”

Sascha Buchanan (2019) made use of participant observation to study the relationship between two fan groups, that of Beyoncé and that of Rihanna. She observed award shows sponsored by iHeartRadio, MTV EMA, and BET that pit one group against another as they competed for Best Fan Army, Biggest Fans, and FANdemonium. Buchanan argues that the media thus sustains a myth of rivalry between the two most commercially successful Black women vocal artists.

Participant Observation

In 2000, a comic writer named Rodney Rothman wanted an insider’s view of white-collar work. He slipped into the sterile, high-rise offices of a New York “dot com” agency. Every day for two weeks, he pretended to work there. His main purpose was simply to see whether anyone would notice him or challenge his presence. No one did. The receptionist greeted him. The employees smiled and said good morning. Rothman was accepted as part of the team. He even went so far as to claim a desk, inform the receptionist of his whereabouts, and attend a meeting. He published an article about his experience in The New Yorker called “My Fake Job” (2000). Later, he was discredited for allegedly fabricating some details of the story and The New Yorker issued an apology. However, Rothman’s entertaining article still offered fascinating descriptions of the inside workings of a “dot com” company and exemplified the lengths to which a writer, or a sociologist, will go to uncover material.

Rothman had conducted a form of study called participant observation , in which researchers join people and participate in a group’s routine activities for the purpose of observing them within that context. This method lets researchers experience a specific aspect of social life. A researcher might go to great lengths to get a firsthand look into a trend, institution, or behavior. A researcher might work as a waitress in a diner, experience homelessness for several weeks, or ride along with police officers as they patrol their regular beat. Often, these researchers try to blend in seamlessly with the population they study, and they may not disclose their true identity or purpose if they feel it would compromise the results of their research.

At the beginning of a field study, researchers might have a question: “What really goes on in the kitchen of the most popular diner on campus?” or “What is it like to be homeless?” Participant observation is a useful method if the researcher wants to explore a certain environment from the inside.

Field researchers simply want to observe and learn. In such a setting, the researcher will be alert and open minded to whatever happens, recording all observations accurately. Soon, as patterns emerge, questions will become more specific, observations will lead to hypotheses, and hypotheses will guide the researcher in analyzing data and generating results.

In a study of small towns in the United States conducted by sociological researchers John S. Lynd and Helen Merrell Lynd, the team altered their purpose as they gathered data. They initially planned to focus their study on the role of religion in U.S. towns. As they gathered observations, they realized that the effect of industrialization and urbanization was the more relevant topic of this social group. The Lynds did not change their methods, but they revised the purpose of their study.

This shaped the structure of Middletown: A Study in Modern American Culture , their published results (Lynd & Lynd, 1929).

The Lynds were upfront about their mission. The townspeople of Muncie, Indiana, knew why the researchers were in their midst. But some sociologists prefer not to alert people to their presence. The main advantage of covert participant observation is that it allows the researcher access to authentic, natural behaviors of a group’s members. The challenge, however, is gaining access to a setting without disrupting the pattern of others’ behavior. Becoming an inside member of a group, organization, or subculture takes time and effort. Researchers must pretend to be something they are not. The process could involve role playing, making contacts, networking, or applying for a job.

Once inside a group, some researchers spend months or even years pretending to be one of the people they are observing. However, as observers, they cannot get too involved. They must keep their purpose in mind and apply the sociological perspective. That way, they illuminate social patterns that are often unrecognized. Because information gathered during participant observation is mostly qualitative, rather than quantitative, the end results are often descriptive or interpretive. The researcher might present findings in an article or book and describe what he or she witnessed and experienced.

This type of research is what journalist Barbara Ehrenreich conducted for her book Nickel and Dimed . One day over lunch with her editor, Ehrenreich mentioned an idea. How can people exist on minimum-wage work? How do low-income workers get by? she wondered. Someone should do a study . To her surprise, her editor responded, Why don’t you do it?

That’s how Ehrenreich found herself joining the ranks of the working class. For several months, she left her comfortable home and lived and worked among people who lacked, for the most part, higher education and marketable job skills. Undercover, she applied for and worked minimum wage jobs as a waitress, a cleaning woman, a nursing home aide, and a retail chain employee. During her participant observation, she used only her income from those jobs to pay for food, clothing, transportation, and shelter.

She discovered the obvious, that it’s almost impossible to get by on minimum wage work. She also experienced and observed attitudes many middle and upper-class people never think about. She witnessed firsthand the treatment of working class employees. She saw the extreme measures people take to make ends meet and to survive. She described fellow employees who held two or three jobs, worked seven days a week, lived in cars, could not pay to treat chronic health conditions, got randomly fired, submitted to drug tests, and moved in and out of homeless shelters. She brought aspects of that life to light, describing difficult working conditions and the poor treatment that low-wage workers suffer.

The book she wrote upon her return to her real life as a well-paid writer, has been widely read and used in many college classrooms.

Ethnography

Ethnography is the immersion of the researcher in the natural setting of an entire social community to observe and experience their everyday life and culture. The heart of an ethnographic study focuses on how subjects view their own social standing and how they understand themselves in relation to a social group.

An ethnographic study might observe, for example, a small U.S. fishing town, an Inuit community, a village in Thailand, a Buddhist monastery, a private boarding school, or an amusement park. These places all have borders. People live, work, study, or vacation within those borders. People are there for a certain reason and therefore behave in certain ways and respect certain cultural norms. An ethnographer would commit to spending a determined amount of time studying every aspect of the chosen place, taking in as much as possible.

A sociologist studying a tribe in the Amazon might watch the way villagers go about their daily lives and then write a paper about it. To observe a spiritual retreat center, an ethnographer might sign up for a retreat and attend as a guest for an extended stay, observe and record data, and collate the material into results.

Institutional Ethnography

Institutional ethnography is an extension of basic ethnographic research principles that focuses intentionally on everyday concrete social relationships. Developed by Canadian sociologist Dorothy E. Smith (1990), institutional ethnography is often considered a feminist-inspired approach to social analysis and primarily considers women’s experiences within male- dominated societies and power structures. Smith’s work is seen to challenge sociology’s exclusion of women, both academically and in the study of women’s lives (Fenstermaker, n.d.).

Historically, social science research tended to objectify women and ignore their experiences except as viewed from the male perspective. Modern feminists note that describing women, and other marginalized groups, as subordinates helps those in authority maintain their own dominant positions (Social Sciences and Humanities Research Council of Canada n.d.). Smith’s three major works explored what she called “the conceptual practices of power” and are still considered seminal works in feminist theory and ethnography (Fensternmaker n.d.).

Sociological Research

The making of middletown: a study in modern u.s. culture.

In 1924, a young married couple named Robert and Helen Lynd undertook an unprecedented ethnography: to apply sociological methods to the study of one U.S. city in order to discover what “ordinary” people in the United States did and believed. Choosing Muncie, Indiana (population about 30,000) as their subject, they moved to the small town and lived there for eighteen months.

Ethnographers had been examining other cultures for decades—groups considered minorities or outsiders—like gangs, immigrants, and the poor. But no one had studied the so-called average American.

Recording interviews and using surveys to gather data, the Lynds objectively described what they observed. Researching existing sources, they compared Muncie in 1890 to the Muncie they observed in 1924. Most Muncie adults, they found, had grown up on farms but now lived in homes inside the city. As a result, the Lynds focused their study on the impact of industrialization and urbanization.

They observed that Muncie was divided into business and working class groups. They defined business class as dealing with abstract concepts and symbols, while working class people used tools to create concrete objects. The two classes led different lives with different goals and hopes. However, the Lynds observed, mass production offered both classes the same amenities. Like wealthy families, the working class was now able to own radios, cars, washing machines, telephones, vacuum cleaners, and refrigerators. This was an emerging material reality of the 1920s.

As the Lynds worked, they divided their manuscript into six chapters: Getting a Living, Making a Home, Training the Young, Using Leisure, Engaging in Religious Practices, and Engaging in Community Activities.

When the study was completed, the Lynds encountered a big problem. The Rockefeller Foundation, which had commissioned the book, claimed it was useless and refused to publish it. The Lynds asked if they could seek a publisher themselves.

Middletown: A Study in Modern American Culture was not only published in 1929 but also became an instant bestseller, a status unheard of for a sociological study. The book sold out six printings in its first year of publication, and has never gone out of print (Caplow, Hicks, & Wattenberg. 2000).

Nothing like it had ever been done before. Middletown was reviewed on the front page of the New York Times. Readers in the 1920s and 1930s identified with the citizens of Muncie, Indiana, but they were equally fascinated by the sociological methods and the use of scientific data to define ordinary people in the United States. The book was proof that social data was important—and interesting—to the U.S. public.

Sometimes a researcher wants to study one specific person or event. A case study is an in-depth analysis of a single event, situation, or individual. To conduct a case study, a researcher examines existing sources like documents and archival records, conducts interviews, engages in direct observation and even participant observation, if possible.

Researchers might use this method to study a single case of a foster child, drug lord, cancer patient, criminal, or rape victim. However, a major criticism of the case study as a method is that while offering depth on a topic, it does not provide enough evidence to form a generalized conclusion. In other words, it is difficult to make universal claims based on just one person, since one person does not verify a pattern. This is why most sociologists do not use case studies as a primary research method.

However, case studies are useful when the single case is unique. In these instances, a single case study can contribute tremendous insight. For example, a feral child, also called “wild child,” is one who grows up isolated from human beings. Feral children grow up without social contact and language, which are elements crucial to a “civilized” child’s development. These children mimic the behaviors and movements of animals, and often invent their own language. There are only about one hundred cases of “feral children” in the world.

As you may imagine, a feral child is a subject of great interest to researchers. Feral children provide unique information about child development because they have grown up outside of the parameters of “normal” growth and nurturing. And since there are very few feral children, the case study is the most appropriate method for researchers to use in studying the subject.

At age three, a Ukranian girl named Oxana Malaya suffered severe parental neglect. She lived in a shed with dogs, and she ate raw meat and scraps. Five years later, a neighbor called authorities and reported seeing a girl who ran on all fours, barking. Officials brought Oxana into society, where she was cared for and taught some human behaviors, but she never became fully socialized. She has been designated as unable to support herself and now lives in a mental institution (Grice 2011). Case studies like this offer a way for sociologists to collect data that may not be obtained by any other method.

Experiments

You have probably tested some of your own personal social theories. “If I study at night and review in the morning, I’ll improve my retention skills.” Or, “If I stop drinking soda, I’ll feel better.” Cause and effect. If this, then that. When you test the theory, your results either prove or disprove your hypothesis.

One way researchers test social theories is by conducting an experiment , meaning they investigate relationships to test a hypothesis—a scientific approach.

There are two main types of experiments: lab-based experiments and natural or field experiments. In a lab setting, the research can be controlled so that more data can be recorded in a limited amount of time. In a natural or field- based experiment, the time it takes to gather the data cannot be controlled but the information might be considered more accurate since it was collected without interference or intervention by the researcher.

As a research method, either type of sociological experiment is useful for testing if-then statements: if a particular thing happens (cause), then another particular thing will result (effect). To set up a lab-based experiment, sociologists create artificial situations that allow them to manipulate variables.

Classically, the sociologist selects a set of people with similar characteristics, such as age, class, race, or education. Those people are divided into two groups. One is the experimental group and the other is the control group. The experimental group is exposed to the independent variable(s) and the control group is not. To test the benefits of tutoring, for example, the sociologist might provide tutoring to the experimental group of students but not to the control group. Then both groups would be tested for differences in performance to see if tutoring had an effect on the experimental group of students. As you can imagine, in a case like this, the researcher would not want to jeopardize the accomplishments of either group of students, so the setting would be somewhat artificial. The test would not be for a grade reflected on their permanent record of a student, for example.

And if a researcher told the students they would be observed as part of a study on measuring the effectiveness of tutoring, the students might not behave naturally. This is called the Hawthorne effect —which occurs when people change their behavior because they know they are being watched as part of a study. The Hawthorne effect is unavoidable in some research studies because sociologists have to make the purpose of the study known. Subjects must be aware that they are being observed, and a certain amount of artificiality may result (Sonnenfeld 1985).

A real-life example will help illustrate the process. In 1971, Frances Heussenstamm, a sociology professor at California State University at Los Angeles, had a theory about police prejudice. To test her theory, she conducted research. She chose fifteen students from three ethnic backgrounds: Black, White, and Hispanic. She chose students who routinely drove to and from campus along Los Angeles freeway routes, and who had had perfect driving records for longer than a year.

Next, she placed a Black Panther bumper sticker on each car. That sticker, a representation of a social value, was the independent variable. In the 1970s, the Black Panthers were a revolutionary group actively fighting racism. Heussenstamm asked the students to follow their normal driving patterns. She wanted to see whether seeming support for the Black Panthers would change how these good drivers were treated by the police patrolling the highways. The dependent variable would be the number of traffic stops/citations.

The first arrest, for an incorrect lane change, was made two hours after the experiment began. One participant was pulled over three times in three days. He quit the study. After seventeen days, the fifteen drivers had collected a total of thirty-three traffic citations. The research was halted. The funding to pay traffic fines had run out, and so had the enthusiasm of the participants (Heussenstamm, 1971).

Secondary Data Analysis

While sociologists often engage in original research studies, they also contribute knowledge to the discipline through secondary data analysis . Secondary data does not result from firsthand research collected from primary sources, but are the already completed work of other researchers or data collected by an agency or organization. Sociologists might study works written by historians, economists, teachers, or early sociologists. They might search through periodicals, newspapers, or magazines, or organizational data from any period in history.

Using available information not only saves time and money but can also add depth to a study. Sociologists often interpret findings in a new way, a way that was not part of an author’s original purpose or intention. To study how women were encouraged to act and behave in the 1960s, for example, a researcher might watch movies, televisions shows, and situation comedies from that period. Or to research changes in behavior and attitudes due to the emergence of television in the late 1950s and early 1960s, a sociologist would rely on new interpretations of secondary data. Decades from now, researchers will most likely conduct similar studies on the advent of mobile phones, the Internet, or social media.

Social scientists also learn by analyzing the research of a variety of agencies. Governmental departments and global groups, like the U.S. Bureau of Labor Statistics or the World Health Organization (WHO), publish studies with findings that are useful to sociologists. A public statistic like the foreclosure rate might be useful for studying the effects of a recession. A racial demographic profile might be compared with data on education funding to examine the resources accessible by different groups.

One of the advantages of secondary data like old movies or WHO statistics is that it is nonreactive research (or unobtrusive research), meaning that it does not involve direct contact with subjects and will not alter or influence people’s behaviors. Unlike studies requiring direct contact with people, using previously published data does not require entering a population and the investment and risks inherent in that research process.

Using available data does have its challenges. Public records are not always easy to access. A researcher will need to do some legwork to track them down and gain access to records. To guide the search through a vast library of materials and avoid wasting time reading unrelated sources, sociologists employ content analysis , applying a systematic approach to record and value information gleaned from secondary data as they relate to the study at hand.

Also, in some cases, there is no way to verify the accuracy of existing data. It is easy to count how many drunk drivers, for example, are pulled over by the police. But how many are not? While it’s possible to discover the percentage of teenage students who drop out of high school, it might be more challenging to determine the number who return to school or get their GED later.

Another problem arises when data are unavailable in the exact form needed or do not survey the topic from the precise angle the researcher seeks. For example, the average salaries paid to professors at a public school is public record. But these figures do not necessarily reveal how long it took each professor to reach the salary range, what their educational backgrounds are, or how long they’ve been teaching.

When conducting content analysis, it is important to consider the date of publication of an existing source and to take into account attitudes and common cultural ideals that may have influenced the research. For example, when Robert S. Lynd and Helen Merrell Lynd gathered research in the 1920s, attitudes and cultural norms were vastly different then than they are now. Beliefs about gender roles, race, education, and work have changed significantly since then. At the time, the study’s purpose was to reveal insights about small U.S. communities. Today, it is an illustration of 1920s attitudes and values.

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How to Conduct Systematic Reviews

• Tight, M. (2019). Systematic reviews and meta-analyses. In Documentary Research in the Social Sciences (pp. 85-94). SAGE Publications Ltd.
• Majchrzak, A., & Markus, M. (2014). Synthesize existing evidence. In Methods for Policy Research: Taking Socially Responsible Action ( Second Edition ed., pp. 40-61). SAGE Publications, Ltd.

Campbell Collaboration Systematic Reviews

• Definition of a Systematic Review
• Campbell Systematic Reviews An open access journal publishing systematic reviews, evidence and gap maps, and methods research papers. Topic areas include: Ageing; Business and Management; Children and Young Persons Wellbeing; Climate Solutions; Crime and Justice; Disability; Education; International Development; Knowledge Translation and Implementation; Methods; Sexual Orientation and Gender Identity; and Social Welfare.

Research Methods Database

• SAGE Research Methods This link opens in a new window SAGE Research Methods provides information on writing a research question, conducting a literature review, choosing a research method, collecting and analyzing data, and writing up the findings. SAGE Research Methods’ coverage spans the full range of research methods used in the social and behavioral sciences, plus a wide range of methods commonly used in science, technology, medicine, and the humanities.

Why conduct systematic reviews?

• Bowers, J., & Testa, P. F. (2019). Better government, better science: The promise of and challenges facing the evidence-informed policy movement. Annual Review of Political Science, 22(1), 521–542.
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Research Methods In Psychology

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

Research methods in psychology are systematic procedures used to observe, describe, predict, and explain behavior and mental processes. They include experiments, surveys, case studies, and naturalistic observations, ensuring data collection is objective and reliable to understand and explain psychological phenomena.

Hypotheses are statements about the prediction of the results, that can be verified or disproved by some investigation.

There are four types of hypotheses :

• Null Hypotheses (H0 ) – these predict that no difference will be found in the results between the conditions. Typically these are written ‘There will be no difference…’
• Alternative Hypotheses (Ha or H1) – these predict that there will be a significant difference in the results between the two conditions. This is also known as the experimental hypothesis.
• One-tailed (directional) hypotheses – these state the specific direction the researcher expects the results to move in, e.g. higher, lower, more, less. In a correlation study, the predicted direction of the correlation can be either positive or negative.
• Two-tailed (non-directional) hypotheses – these state that a difference will be found between the conditions of the independent variable but does not state the direction of a difference or relationship. Typically these are always written ‘There will be a difference ….’

All research has an alternative hypothesis (either a one-tailed or two-tailed) and a corresponding null hypothesis.

Once the research is conducted and results are found, psychologists must accept one hypothesis and reject the other. 

So, if a difference is found, the Psychologist would accept the alternative hypothesis and reject the null.  The opposite applies if no difference is found.

Sampling techniques

Sampling is the process of selecting a representative group from the population under study.

A sample is the participants you select from a target population (the group you are interested in) to make generalizations about.

Representative means the extent to which a sample mirrors a researcher’s target population and reflects its characteristics.

Generalisability means the extent to which their findings can be applied to the larger population of which their sample was a part.

• Volunteer sample : where participants pick themselves through newspaper adverts, noticeboards or online.
• Opportunity sampling : also known as convenience sampling , uses people who are available at the time the study is carried out and willing to take part. It is based on convenience.
• Random sampling : when every person in the target population has an equal chance of being selected. An example of random sampling would be picking names out of a hat.
• Systematic sampling : when a system is used to select participants. Picking every Nth person from all possible participants. N = the number of people in the research population / the number of people needed for the sample.
• Stratified sampling : when you identify the subgroups and select participants in proportion to their occurrences.
• Snowball sampling : when researchers find a few participants, and then ask them to find participants themselves and so on.
• Quota sampling : when researchers will be told to ensure the sample fits certain quotas, for example they might be told to find 90 participants, with 30 of them being unemployed.

Experiments always have an independent and dependent variable .

• The independent variable is the one the experimenter manipulates (the thing that changes between the conditions the participants are placed into). It is assumed to have a direct effect on the dependent variable.
• The dependent variable is the thing being measured, or the results of the experiment.

Operationalization of variables means making them measurable/quantifiable. We must use operationalization to ensure that variables are in a form that can be easily tested.

For instance, we can’t really measure ‘happiness’, but we can measure how many times a person smiles within a two-hour period. 

By operationalizing variables, we make it easy for someone else to replicate our research. Remember, this is important because we can check if our findings are reliable.

Extraneous variables are all variables which are not independent variable but could affect the results of the experiment.

It can be a natural characteristic of the participant, such as intelligence levels, gender, or age for example, or it could be a situational feature of the environment such as lighting or noise.

Demand characteristics are a type of extraneous variable that occurs if the participants work out the aims of the research study, they may begin to behave in a certain way.

For example, in Milgram’s research , critics argued that participants worked out that the shocks were not real and they administered them as they thought this was what was required of them. 

Extraneous variables must be controlled so that they do not affect (confound) the results.

Randomly allocating participants to their conditions or using a matched pairs experimental design can help to reduce participant variables. 

Situational variables are controlled by using standardized procedures, ensuring every participant in a given condition is treated in the same way

Experimental Design

Experimental design refers to how participants are allocated to each condition of the independent variable, such as a control or experimental group.

• Independent design ( between-groups design ): each participant is selected for only one group. With the independent design, the most common way of deciding which participants go into which group is by means of randomization. 
• Matched participants design : each participant is selected for only one group, but the participants in the two groups are matched for some relevant factor or factors (e.g. ability; sex; age).
• Repeated measures design ( within groups) : each participant appears in both groups, so that there are exactly the same participants in each group.
• The main problem with the repeated measures design is that there may well be order effects. Their experiences during the experiment may change the participants in various ways.
• They may perform better when they appear in the second group because they have gained useful information about the experiment or about the task. On the other hand, they may perform less well on the second occasion because of tiredness or boredom.
• Counterbalancing is the best way of preventing order effects from disrupting the findings of an experiment, and involves ensuring that each condition is equally likely to be used first and second by the participants.

If we wish to compare two groups with respect to a given independent variable, it is essential to make sure that the two groups do not differ in any other important way. 

Experimental Methods

All experimental methods involve an iv (independent variable) and dv (dependent variable)..

• Field experiments are conducted in the everyday (natural) environment of the participants. The experimenter still manipulates the IV, but in a real-life setting. It may be possible to control extraneous variables, though such control is more difficult than in a lab experiment.
• Natural experiments are when a naturally occurring IV is investigated that isn’t deliberately manipulated, it exists anyway. Participants are not randomly allocated, and the natural event may only occur rarely.

Case studies are in-depth investigations of a person, group, event, or community. It uses information from a range of sources, such as from the person concerned and also from their family and friends.

Many techniques may be used such as interviews, psychological tests, observations and experiments. Case studies are generally longitudinal: in other words, they follow the individual or group over an extended period of time. 

Case studies are widely used in psychology and among the best-known ones carried out were by Sigmund Freud . He conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.

Case studies provide rich qualitative data and have high levels of ecological validity. However, it is difficult to generalize from individual cases as each one has unique characteristics.

Correlational Studies

Correlation means association; it is a measure of the extent to which two variables are related. One of the variables can be regarded as the predictor variable with the other one as the outcome variable.

Correlational studies typically involve obtaining two different measures from a group of participants, and then assessing the degree of association between the measures. 

The predictor variable can be seen as occurring before the outcome variable in some sense. It is called the predictor variable, because it forms the basis for predicting the value of the outcome variable.

Relationships between variables can be displayed on a graph or as a numerical score called a correlation coefficient.

• If an increase in one variable tends to be associated with an increase in the other, then this is known as a positive correlation .
• If an increase in one variable tends to be associated with a decrease in the other, then this is known as a negative correlation .
• A zero correlation occurs when there is no relationship between variables.

After looking at the scattergraph, if we want to be sure that a significant relationship does exist between the two variables, a statistical test of correlation can be conducted, such as Spearman’s rho.

The test will give us a score, called a correlation coefficient . This is a value between 0 and 1, and the closer to 1 the score is, the stronger the relationship between the variables. This value can be both positive e.g. 0.63, or negative -0.63.

A correlation between variables, however, does not automatically mean that the change in one variable is the cause of the change in the values of the other variable. A correlation only shows if there is a relationship between variables.

Correlation does not always prove causation, as a third variable may be involved. 

Interview Methods

Interviews are commonly divided into two types: structured and unstructured.

A fixed, predetermined set of questions is put to every participant in the same order and in the same way. 

Responses are recorded on a questionnaire, and the researcher presets the order and wording of questions, and sometimes the range of alternative answers.

The interviewer stays within their role and maintains social distance from the interviewee.

There are no set questions, and the participant can raise whatever topics he/she feels are relevant and ask them in their own way. Questions are posed about participants’ answers to the subject

Unstructured interviews are most useful in qualitative research to analyze attitudes and values.

Though they rarely provide a valid basis for generalization, their main advantage is that they enable the researcher to probe social actors’ subjective point of view. 

Questionnaire Method

Questionnaires can be thought of as a kind of written interview. They can be carried out face to face, by telephone, or post.

The choice of questions is important because of the need to avoid bias or ambiguity in the questions, ‘leading’ the respondent or causing offense.

• Open questions are designed to encourage a full, meaningful answer using the subject’s own knowledge and feelings. They provide insights into feelings, opinions, and understanding. Example: “How do you feel about that situation?”
• Closed questions can be answered with a simple “yes” or “no” or specific information, limiting the depth of response. They are useful for gathering specific facts or confirming details. Example: “Do you feel anxious in crowds?”

Its other practical advantages are that it is cheaper than face-to-face interviews and can be used to contact many respondents scattered over a wide area relatively quickly.

Observations

There are different types of observation methods :

• Covert observation is where the researcher doesn’t tell the participants they are being observed until after the study is complete. There could be ethical problems or deception and consent with this particular observation method.
• Overt observation is where a researcher tells the participants they are being observed and what they are being observed for.
• Controlled : behavior is observed under controlled laboratory conditions (e.g., Bandura’s Bobo doll study).
• Natural : Here, spontaneous behavior is recorded in a natural setting.
• Participant : Here, the observer has direct contact with the group of people they are observing. The researcher becomes a member of the group they are researching.  
• Non-participant (aka “fly on the wall): The researcher does not have direct contact with the people being observed. The observation of participants’ behavior is from a distance

Pilot Study

A pilot  study is a small scale preliminary study conducted in order to evaluate the feasibility of the key s teps in a future, full-scale project.

A pilot study is an initial run-through of the procedures to be used in an investigation; it involves selecting a few people and trying out the study on them. It is possible to save time, and in some cases, money, by identifying any flaws in the procedures designed by the researcher.

A pilot study can help the researcher spot any ambiguities (i.e. unusual things) or confusion in the information given to participants or problems with the task devised.

Sometimes the task is too hard, and the researcher may get a floor effect, because none of the participants can score at all or can complete the task – all performances are low.

The opposite effect is a ceiling effect, when the task is so easy that all achieve virtually full marks or top performances and are “hitting the ceiling”.

Research Design

In cross-sectional research , a researcher compares multiple segments of the population at the same time

Sometimes, we want to see how people change over time, as in studies of human development and lifespan. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time.

In cohort studies , the participants must share a common factor or characteristic such as age, demographic, or occupation. A cohort study is a type of longitudinal study in which researchers monitor and observe a chosen population over an extended period.

Triangulation means using more than one research method to improve the study’s validity.

Reliability

Reliability is a measure of consistency, if a particular measurement is repeated and the same result is obtained then it is described as being reliable.

• Test-retest reliability :  assessing the same person on two different occasions which shows the extent to which the test produces the same answers.
• Inter-observer reliability : the extent to which there is an agreement between two or more observers.

Meta-Analysis

A meta-analysis is a systematic review that involves identifying an aim and then searching for research studies that have addressed similar aims/hypotheses.

This is done by looking through various databases, and then decisions are made about what studies are to be included/excluded.

Strengths: Increases the conclusions’ validity as they’re based on a wider range.

Weaknesses: Research designs in studies can vary, so they are not truly comparable.

Peer Review

A researcher submits an article to a journal. The choice of the journal may be determined by the journal’s audience or prestige.

The journal selects two or more appropriate experts (psychologists working in a similar field) to peer review the article without payment. The peer reviewers assess: the methods and designs used, originality of the findings, the validity of the original research findings and its content, structure and language.

Feedback from the reviewer determines whether the article is accepted. The article may be: Accepted as it is, accepted with revisions, sent back to the author to revise and re-submit or rejected without the possibility of submission.

The editor makes the final decision whether to accept or reject the research report based on the reviewers comments/ recommendations.

Peer review is important because it prevent faulty data from entering the public domain, it provides a way of checking the validity of findings and the quality of the methodology and is used to assess the research rating of university departments.

Peer reviews may be an ideal, whereas in practice there are lots of problems. For example, it slows publication down and may prevent unusual, new work being published. Some reviewers might use it as an opportunity to prevent competing researchers from publishing work.

Some people doubt whether peer review can really prevent the publication of fraudulent research.

The advent of the internet means that a lot of research and academic comment is being published without official peer reviews than before, though systems are evolving on the internet where everyone really has a chance to offer their opinions and police the quality of research.

Types of Data

• Quantitative data is numerical data e.g. reaction time or number of mistakes. It represents how much or how long, how many there are of something. A tally of behavioral categories and closed questions in a questionnaire collect quantitative data.
• Qualitative data is virtually any type of information that can be observed and recorded that is not numerical in nature and can be in the form of written or verbal communication. Open questions in questionnaires and accounts from observational studies collect qualitative data.
• Primary data is first-hand data collected for the purpose of the investigation.
• Secondary data is information that has been collected by someone other than the person who is conducting the research e.g. taken from journals, books or articles.

Validity means how well a piece of research actually measures what it sets out to, or how well it reflects the reality it claims to represent.

Validity is whether the observed effect is genuine and represents what is actually out there in the world.

• Concurrent validity is the extent to which a psychological measure relates to an existing similar measure and obtains close results. For example, a new intelligence test compared to an established test.
• Face validity : does the test measure what it’s supposed to measure ‘on the face of it’. This is done by ‘eyeballing’ the measuring or by passing it to an expert to check.
• Ecological validit y is the extent to which findings from a research study can be generalized to other settings / real life.
• Temporal validity is the extent to which findings from a research study can be generalized to other historical times.

Features of Science

• Paradigm – A set of shared assumptions and agreed methods within a scientific discipline.
• Paradigm shift – The result of the scientific revolution: a significant change in the dominant unifying theory within a scientific discipline.
• Objectivity – When all sources of personal bias are minimised so not to distort or influence the research process.
• Empirical method – Scientific approaches that are based on the gathering of evidence through direct observation and experience.
• Replicability – The extent to which scientific procedures and findings can be repeated by other researchers.
• Falsifiability – The principle that a theory cannot be considered scientific unless it admits the possibility of being proved untrue.

Statistical Testing

A significant result is one where there is a low probability that chance factors were responsible for any observed difference, correlation, or association in the variables tested.

If our test is significant, we can reject our null hypothesis and accept our alternative hypothesis.

If our test is not significant, we can accept our null hypothesis and reject our alternative hypothesis. A null hypothesis is a statement of no effect.

In Psychology, we use p < 0.05 (as it strikes a balance between making a type I and II error) but p < 0.01 is used in tests that could cause harm like introducing a new drug.

A type I error is when the null hypothesis is rejected when it should have been accepted (happens when a lenient significance level is used, an error of optimism).

A type II error is when the null hypothesis is accepted when it should have been rejected (happens when a stringent significance level is used, an error of pessimism).

Ethical Issues

• Informed consent is when participants are able to make an informed judgment about whether to take part. It causes them to guess the aims of the study and change their behavior.
• To deal with it, we can gain presumptive consent or ask them to formally indicate their agreement to participate but it may invalidate the purpose of the study and it is not guaranteed that the participants would understand.
• Deception should only be used when it is approved by an ethics committee, as it involves deliberately misleading or withholding information. Participants should be fully debriefed after the study but debriefing can’t turn the clock back.
• All participants should be informed at the beginning that they have the right to withdraw if they ever feel distressed or uncomfortable.
• It causes bias as the ones that stayed are obedient and some may not withdraw as they may have been given incentives or feel like they’re spoiling the study. Researchers can offer the right to withdraw data after participation.
• Participants should all have protection from harm . The researcher should avoid risks greater than those experienced in everyday life and they should stop the study if any harm is suspected. However, the harm may not be apparent at the time of the study.
• Confidentiality concerns the communication of personal information. The researchers should not record any names but use numbers or false names though it may not be possible as it is sometimes possible to work out who the researchers were.

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• Estimates and cost for people and software resources
• Potential risks, assumptions, and blockers
• Dependencies
• Project teams (roles and workflows)
• Change process requirements
• Success criteria
• Did we mention dependencies?

👾 Phase 3: Execution

Dependencies are an absolute necessity for controlled project execution . If you’re a coffee person and you skip your morning cup and head straight to work, chances are, you make your day a little more difficult than it should be.

As you’re on the path to assigning individual tasks, have an open discussion with the project team about what can or can’t be started until a specific task is completed. You’ll save time and money with transparency and set everyone up for success from start to finish.

👾 Phase 4: Monitoring

Data is your north star metric to manage people, resources, budgets , and risks during the execution phase. Make sure you’re using a powerful productivity tool like ClickUp to know what project contributors are working on and what they need to do next.

Even more, track project goals and communicate with stakeholders and clients within ClickUp.

👾 Phase 5: Closing

After you turn in the final deliverables and wrap up loose ends, it’s advantageous to assess the performance of team members and resources. This reflection period will help improve the next project.

Have all deliverables been completed, validated, and archived?

Were issues and risks effectively managed?

Which processes were easy/challenging, and what would they change?

Relate: Project Management Examples !

Welcome to your pocket encyclopedia of the top 18 project management methodologies! 📘

A nod to agile project management methodology, the adaptive project framework is an iterative approach to satisfy a project’s goals and outcomes. Meaning, a project’s plan is broken into short iterations (or cycles) of tasks. This helps structure task dependencies and establishes clear deadlines.

The five steps in the adaptive project framework are:

• Project Scope : document the project plan with a project charter (download ClickUp’s Project Charter Template )
• Cycle Plan: define each task with all dependencies
• Cycle Completion : after one cycle completes, another begins
• Control Point : the client or stakeholder meets with the team to assess the quality and potential room for improvements in the next cycle
• Final Report : determines if results were achieved and successful

🟢 Adaptive Project Framework Pros

• Less time is spent on the first phase (defining project scope)
• Client and stakeholder satisfaction increases because of their involvement
• Teams create the most value with learnings in short cycles

🟡 Adaptive Project Framework Cons

• The project scope will potentially change throughout the lifecycle, reverting from a client or stakeholder’s original vision
• Too much flexibility for teams accustomed to fixed schedules
• Limited control over business processes

The hybrid model is the best of both Agile and Waterfall methods . Commonly used in product development companies, the planning phase uses waterfall method techniques but applies agile practices during execution .

🟢 Agifall/Hybrid Pros

• Continous collaboration and communication amongst different teams within a project
• A gateway to a complete transition into Agile methodology
• Using the best techniques of both methods to create a custom approach

🟡 Agifall/Hybrid Cons

• A good amount of time is required to plan a clear, clean, and understandable project approach

Today, one of the most popular project management methodologies, the agile methodology , is an incremental and iterative approach to managing projects in phases . Each iteration has a fixed scope (between 1-3 weeks) to maintain product release consistency, stability, and on-time delivery.

At its core, release management minimizes risks, tracks and audits requirements , and secures consistent implementation—in the least disruptive approach .

The five steps in the Agile methodology are:

• Defining the release plan and product roadmap
• Designing and building product feature(s)
• Testing and iterating
• Closing and maintenance

🟢 Agile Pros

• Increases customer satisfaction and retention
• Software code and testing standards are used repeatedly
• Specific roles with multiple project drivers to meet the same goal

🟡 Agile Cons

• Some organizations might find agile workflows to be a poor culture fit
• Potential lack of understanding in workflow flexibility
• An experienced agile professional might be necessary for teams new to agile

Project managers use the Critical Path Method to define the critical and non-critical tasks for timely delivery. After listing every activity and task required for completion, they will note dependencies and write a sequence of times for each.

Planning with the Critical Path Method allows teams to pinpoint opportunities to shorten task times and flag potential shifts when changes can affect critical tasks.

🟢 Critical Path Method Pros

• Identifies the most important activities and tasks in a project
• Displays the complexities of whether a project is small or substantial
• Easily explained with a chart or graph

🟡 Critical Path Method Cons

• Mid-changes could disrupt the overall stability of the project
• Requires time and effort to build the CPM chart successfully
• Client and stakeholders must be comfortable with estimates on progress and delivery

Note : Critical Chain Project Management, a related project management methodology, focuses on managing resources and buffer duration between task chains and improving upon the Critical Path Method.

Test out these critical path templates !

The eXtreme Programming methodology takes elements of traditional software engineering practices to, well, extreme levels. However, it’s familiar to the agile framework like specific planning approach, on-site customer participation, and continuous testing.

Standard software development practices found in the eXtreme Programming method are:

• Pair Programming : two developers work together simultaneously on code
• Refactoring : implementing a feature without changing the behavior of the system
• Continuous Integration : integrating as soon as you identify issues decreases the number of bugs that could arise in production
• Short Release Cycles: every day is optimized, so by the end of the cycle, tested features are deployed for customer feedback
• The Planning Game : Customer and developers meet to discuss the upcoming release
• 40-Hour Week: developers must work fast and efficiently to maintain product quality, so keeping to a manageable work supports a healthy work-life balance
• Non-Complex Design : when design complications are found, it’s removed so developers can articulate product intention

🟢 eXtreme Programming Pros

• Fixed timeline length, typically 1-2 weeks
• Flexible to changes during the sprint cycle
• Higher customer satisfaction

🟡 eXtreme Programming Cons

• Requires engaged customer(s) to make informed project decisions
• Stressful if teams don’t fully understand the demanding workflow
• Geared towards product delivery businesses

The GTD (Get Things Done) method is a project management methodology less concerned with technical activities such as coding and testing. Instead, it emphasizes personal productivity to create the best systems for approaching life and work.

The five simple steps in the GTD method are:

• Capture : record your notes to make room for more headspace
• Clarify : review your notes and determine whether they should be converted into tasks, filed for referenced, or tossed
• Organize : dedicate a single place for your collection of ideas and tasks
• Reflect : visit your collection frequently to update for relevancy and opportunities
• Engage : use the system you’ve built to take action on your items

If you’re looking for a productivity tool to help gather your thoughts, tasks, schedule, and workflow in one place, learn how to use ClickUp with the GTD project management methodology. ⬇️

🟢 Get Things Done Pros

• Large or intimidating projects are broken down into manageable tasks
• Easily view which tasks take priority over others
• Entirely customizable for whatever season of life and work you’re in

🟡 Get Things Done Cons

• Requires time to set up a system for long term success
• Recording changes with the most up to date information are necessary to prevent backtracking

Check out these GTD apps !

The Integrated Project Management (IPM) project management methodology oversees the cross-functional communication and hand-off during all project phases . Since cross-functional teams have different processes and workflows, IPM helps resolve schedule conflicts, bottlenecks, and team bandwidths.

👉 Check out these project management communication resources to assist with Integrated Project Management planning:

• 7 Project Management Challenges And How To Solve Them
• How Toyin Olasehinde Uses ClickUp Comments to Streamline Communication
• 20+ Project Management Tips for Marketers
• Here’s How To Improve Your Team Communication
• 16 Unmissable Benefits of Project Management Software

🟢 Integrated Project Management Pros

• Projects are appropriately monitored and controlled
• Productivity accelerates to complete projects on time
• Complex resource planning becomes simple

🟡 Integrated Project Management Cons

• No cons to cohesive team communication and collaboration! 🤝

The Lean project management methodology focuses on tools and practices heavily centered on product value for customers . The commitment to constantly improve the reliability and quality of products helps businesses deliver faster . In addition, understanding the specific tasks and activities that need to be completed at a given time minimizes the chances of wasting time and resources.

The five principles of lean methodology are:

• Define Value : align processes to deliver on customer needs
• Map the Value Stream : remove barriers that disrupt the flow
• Create Flow : manage team member workloads and production steps to maintain a smooth process
• Establish Pull: remove overproduction of inventory by implementing a system for on-demand delivery
• Seek Perfection : continuously improve to make steps towards eliminating all mistakes

🟢 Lean Pros

• Understands all aspects of customer demands
• Promotes involving team members closest to the work
• Removes inventory waste, process barriers, and defective products

🟡 Lean Cons

• Not suitable for teams that don’t use a dashboard tool
• Not a culture fit for organizations resistant towards full transparency
• Experienced resource management professionals might be necessary for some teams

Bonus: Lean vs. Agile Project Management 💜

The New Product Introduction methodology is used by companies that continuously release new products . NPI streamlines time and efforts to achieve desired results by carefully vetting new ideas and surveying customers .

The six phases of New Product Introduction are:

• Ideation : brainstorming a product concept influenced by business risk and market research
• Product Definition : gathering product requirements
• Prototyping : building a model for the hardware or software product for performance analysis
• Detailed Design : refining the product model and fully designing to its final form
• Pre-Production (Validation/Testing) : validating the product to ensure high-performance results
• Manufacturing : all design, marketing, and sales efforts are carried out to deliver the final product

🟢 New Product Introduction Pros

• Creates a culture of development
• Drives higher value proposition
• Increases opportunities for businesses to innovate and grow within their industry

🟡 New Product Introduction Cons

• Not suitable for projects that are small in scale
• Product ideas can fail unexpectedly

The Outcome Mapping methodology is an approach for planning, monitoring, and evaluation developed by the International Development Research Centre (IDRC) , a Canadian grant-making organization. It’s distinct from all other methodologies mentioned in this list because it focuses on behavior changes of people and groups the project or program works with directly . (Organizations within policy development and research communication typically use this method.)

Outcome Mapping blends social learning, self-assessment, and adaptive management within an organization. The process allows organizations to gather data and encourage reflection about development impacts.

The three stages of Outcome Mapping are:

• Intentional Design : determining the vision, partners, tangible changes (outcomes), and contribution efforts
• Outcome and Performance Monitoring : using an Outcome Journal (tracking progress markers), Strategy Journal (testing strategy in wavering circumstances), and Performance Journal (recording practices and opportunities for improvement) to provide data
• Evaluation Planning : a detailed progress review to influence an evaluation plan and bring strategic benefits to the project

🟢 Outcome Mapping Pros

• Successful results contribute to sustainable improvements
• Incorporates being reflective about organizational and social learnings
• Flexible model to tailor to project needs

🟡 Outcome Mapping Cons

• Requires organizations to take a hard look at their views about development
• Regular communication and participation is necessary for success
• Not suitable for short software development lifecycles

The Package Enabled Reengineering methodology focuses on the original functionality of software packages as a framework for rethinking the design. It requires an analysis of challenges within the current process, management, people, and design to shape new systems.

Check out how to jumpstart your management and design workflows in ClickUp so you can organize your planning with the PER project management methodology. ⬇️

🟢 Package Enabled Reengineering Pros

• Optimizes productivity, resources, and communication strategically

🟡 Package Enabled Reengineering Cons

• Not suitable for organizations with already successful systems

Written by the Project Management Institute, a global “for-purpose” organization , the Project Management Body of Knowledge is a collection of tools, techniques , and best practices for a project manager to align with the evolving changes of project management.

🟢 PMI’s PMBOK Pros

• Resource for project managers studying for project management certification : CAPM (Certified Associate in Project Management) or PMP (Project Management Professional)
• Includes practices guides and comprehensive project management terms glossary

🟡 PMI’s PMBOK Cons

• Extensive 700+ page book not meant for reading cover to cover

The PRINCE2 project management methodology is globally adopted because of its practical and adaptive framework to divide projects into controllable stages . It focuses on an orderly approach in a project’s lifespan from beginning to end. The PRINCE2 methodology directly impacts day-to-day routines to deliver successful projects, from construction development projects to launching social campaigns.

🟢 PRINCE2 Pros

• PRINCE2 certification is available
• Improves project management skills with proven best practices
• Adapts to any project type and scale

🟡 PRINCE2 Cons

• Documentation heavy
• Without certification or experience, it might take longer to see results

The Rational Unified Process methodology is built on well-documented software processes focusing on an iterative approach throughout development. This allows for quick changes on high-risks throughout every stage . As a result, RUP’s structure lends itself to assembling high-quality software production .

The four project phases are:

• Inception : outlining the scope of work or statement of work , impact analysis, identify key use cases, and cost estimates
• Elaboration : designing an architected foundation for the product
• Construction : completing the bulk of the work to develop all software components
• Transition : introducing the product to the end-users, handling bug issues, and reviewing outcome goals

🟢 Rational Unified Process Pros

• Reduces time for initial integration as it’s built in the project stages
• Repeatable steps to apply to future projects
• Emphasizes documentation

🟡 Rational Unified Process Cons

• Not suitable for teams that are unable to keep up with documentation
• The project’s success rate is higher with experienced team members

Scrum project management adds to the agile approach by including a prominent role called the Scrum Master. The Scrum Master conducts a sprint planning meeting with the Product Owner and Development team. Then, they select the high-priority items from the Product Backlog —a list of collected feedback from customers and stakeholders—to release in one sprint. These high-priority items become a Sprint Backlog for the development team to build, test, and release.

Throughout the sprint cycle, a daily scrum meeting is held (typically at the start of the workday) for each project contributor to share: what they did yesterday, what they will do today, and any blockers in the way.

At the end of the sprint, a Sprint Review meeting is held with the Scrum Master, Product Owner, stakeholders, and development team to walk through accomplishments and changes. This review helps improve the performance of future sprints .

🟢 Scrum Pros

• Flexible timeline length, typically 2-4 weeks
• Teams are aligned around tasks and progress through daily scrum meetings
• Short sprints support faster changes from customer and stakeholder feedback

🟡 Scrum Cons

• Daily meetings might not be a culture fit for some teams
• The success rate is higher with experienced agile team members
• Adopting the Scrum framework in larger teams is difficult

Scrumban is the combination of Scrum and Kanban. Kanban adds metric visuals and process improvements to the Scrum methodology. For example, a distinct feature of the Scrumban method is the WIP (work in progress) board to help visualize all tasks from start to finish .

This board, divided into three sections—product backlog, work in progress, and completed—shows the collective work in a given section . With this data, the Scrum team can make adjustments to monitor workloads.

🟢 Scrumban Pros

• Adds a process improvement attribute to the Scrum methodology
• Issues can be pinpointed and resolved quickly on a progress board
• Promotes full transparency for all project team members

🟡 Scrumban Cons

• Boards that are not updated in real-time cause delay and confusion
• A fairly new methodology
• Daily standups are optional, which can be an advantage or disadvantage to a preferred workflow

Motorola introduced the Six Sigma methodology in the 1980s to bring down the defects in its manufacturing process. However, it’s suitable for all industries . It emphasizes a data-driven approach for continuous business transformation . Six means six standard deviations (a statistical benchmark), and the sigma symbol represents a standard deviation.

There are two models of the six sigma methodology:

Six Sigma DMAIC

• D efine the current problem, goals, and deliverables
• M easure the current process and performance
• A nalyze the causes of the problem
• Improve the process by proposing and testing solutions
• C ontrol the outcome by implementing changes in place if problems arise

Six Sigma DMADV

• D esign a process that meets customer expectations and needs
• V erify the design meets customer needs and it’s appropriately

The DMAIC and DMADV models in the six sigma methodology ensure each step is followed to achieve the best results.

🟢 Six Sigma Pros

• Reduces wastes and costs
• Enhances value and improves the quality of a company’s output
• Six Sigma certification is available

🟡 Six Sigma Cons

• An implementation period is necessary for success
• Complicated and requires statistical analysis
• It can get costly in the long run

Bonus: Check out the Top 10 Six Sigma Templates

The Waterfall methodology is one of the traditional project management methods. It has two main attributes: thorough initial planning and fixed-end requirements . Waterfall project management is predictive , meaning each stage starts when its predecessor ends. After a project has begun, it’s nearly impossible to make changes. (This characteristic of Waterfall is off-putting for organizations that experience altering project requirements while in progress.)

On the flip side, for businesses that need predicted outcomes , such as construction and manufacturing, this rigid framework is the best approach for their needs.

The stages of the Waterfall methodology are:

• Requirements Gathering
• Development

🟢 Waterfall Pros

• Easy and familiar to understand for new and seasoned teams
• No overlap between project phases
• Clear deadlines are determined and adhered to at the start of the project

Check out our Waterfall Management Template !

🟡 Waterfall Cons

• Top-down communication model
• Not suitable for software development or complex projects
• Not best for ongoing projects

Now that you know your best project methodologies options, where can you keep your people, processes, and projects organized? 🤔

One of the best ways to add value to your work and optimize your time is to use a software tool. Our recommendation? ClickUp! ✨

ClickUp is the ultimate productivity platform allowing teams to manage projects, collaborate smarter, and bring all work under one tool. Here are a few ClickUp features among the hundreds available that can be customized to any team size for consistent collaboration:

📊 Dashboards

ClickUp Dashboards are a time-saving resource to share high-level views with project stakeholders or project progress with anyone in their Workspace! Track sprints, task progress, portfolio management, and more with customizable widgets. 

A must-have tool for these project management methodologies:

• Rational Unified Process
• Adaptive project framework (APF)

🤖 Automations

With ClickUp Automations , you’re able to set up combinations of Triggers and Actions to help automate repetitive actions—saving time and allowing you to focus on things that matter. Does your team use workflow software with external applications like GitHub? Automate your workflow within ClickUp using the GitHub integration ! 

🗒 List view

ClickUp’s powerful and flexible List view can sort, filter, or group columns in any way. Columns can be customized to show important information—task assignees, start and due dates, project briefs , website links, task comments—it’s up to you!

Subtasks in ClickUp add a layer to your work structure, allowing you to define more detailed goals inside of your tasks. This is a perfect solution for: action items that don’t warrant a new task, objectives that need to be completed to finish an overall task, and task dependencies. 

🏃‍♀️ Sprint

Sprints in ClickUp are packed with additional ClickUp features to help teams better understand and manage their product roadmaps. Available on every ClickUp plan, Sprints use tasks as items of work so teams don’t have to rely on other software to get their work done. 

🟫 Board view

Choose whether you want to zoom in on a single List, an entire Folder, or even all Spaces across your Workspace in Board view . For teams that prefer Kanban project management, Board’s view powerful drag-and-drop interface is perfect for visualizing tasks in progress. 

ClickUp: A Powerful and Friendly Tool 

Your ClickUp Workspace can be fully customized to optimize any project management methodology so you can do your best work and take it anywhere you go . Change the way you build and manage projects with ClickUp today!

Questions? Comments? Visit our Help Center for support.

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Which social media platforms are most common, who uses each social media platform, find out more, social media fact sheet.

Many Americans use social media to connect with one another, engage with news content, share information and entertain themselves. Explore the patterns and trends shaping the social media landscape.

To better understand Americans’ social media use, Pew Research Center surveyed 5,733 U.S. adults from May 19 to Sept. 5, 2023. Ipsos conducted this National Public Opinion Reference Survey (NPORS) for the Center using address-based sampling and a multimode protocol that included both web and mail. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race and ethnicity, education and other categories.

Polls from 2000 to 2021 were conducted via phone. For more on this mode shift, read our Q&A.

Here are the questions used for this analysis , along with responses, and  its methodology ­­­.

A note on terminology: Our May-September 2023 survey was already in the field when Twitter changed its name to “X.” The terms  Twitter  and  X  are both used in this report to refer to the same platform.

YouTube and Facebook are the most-widely used online platforms. About half of U.S. adults say they use Instagram, and smaller shares use sites or apps such as TikTok, LinkedIn, Twitter (X) and BeReal.

Note: The vertical line indicates a change in mode. Polls from 2012-2021 were conducted via phone. In 2023, the poll was conducted via web and mail. For more details on this shift, please read our Q&A . Refer to the topline for more information on how question wording varied over the years. Pre-2018 data is not available for YouTube, Snapchat or WhatsApp; pre-2019 data is not available for Reddit; pre-2021 data is not available for TikTok; pre-2023 data is not available for BeReal. Respondents who did not give an answer are not shown.

Source: Surveys of U.S. adults conducted 2012-2023.

Usage of the major online platforms varies by factors such as age, gender and level of formal education.

% of U.S. adults who say they ever use __ by …

• RACE & ETHNICITY
• POLITICAL AFFILIATION

This fact sheet was compiled by Research Assistant  Olivia Sidoti , with help from Research Analyst  Risa Gelles-Watnick , Research Analyst  Michelle Faverio , Digital Producer  Sara Atske , Associate Information Graphics Designer Kaitlyn Radde and Temporary Researcher  Eugenie Park .

Follow these links for more in-depth analysis of the impact of social media on American life.

• Americans’ Social Media Use  Jan. 31, 2024
• Americans’ Use of Mobile Technology and Home Broadband  Jan. 31 2024
• Q&A: How and why we’re changing the way we study tech adoption  Jan. 31, 2024

Find more reports and blog posts related to  internet and technology .

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ABOUT PEW RESEARCH CENTER  Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of  The Pew Charitable Trusts .

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