how to write assumptions in research example

How to Write Assumptions for a Thesis

Kristina barroso, 25 jun 2018.

They say that when you assume, you make a “donkey” out of “you” and “me.” As a result, making assumptions in everyday life does not typically yield positive results. When it comes to research for a thesis or dissertation, though, assumptions are a critical part of the work’s foundation. Assumptions in a thesis are things that your readers will generally accept as either true or plausible, such as the assumption of honest responses from study participants.

Explore this article

• The Importance of Assumptions in a Thesis
• The Importance of a Structured Thesis
• Identifying Assumptions
• Common Assumptions

1 The Importance of Assumptions in a Thesis

One of the first and most important tasks when writing a thesis is to decide what assumptions your readers are likely to have. Research is built on assumptions, which is why they are so important and necessary for your study to be valid and credible. The research problem itself cannot exist without assumptions because those assumptions directly influence what kind of inferences you can reasonably draw from your research.

2 The Importance of a Structured Thesis

A structured thesis is the roadmap for a structured paper. Your thesis statement should clearly present the central argument, and outline the structure that the rest of the paper will follow. You cannot write a thesis statement without knowing which assumptions you are basing the research problem on.

3 Identifying Assumptions

Making incorrect or unreasonable assumptions will likely result in drawing false conclusions based on those flawed assumptions, which is why it is so important to think critically about which assumptions you should or should not be making in your research efforts. A good assumption is one that can be verified or reasonably justified. A bad assumption, on the other hand, is not easily verified or reasonably justified. To ensure that you are making good assumptions, you must do more than simply state what they are. Explain and give examples of why your assumptions are probably true. For example, if you are assuming that participants will provide honest responses to your questions, explain the data collection process and how you will preserve anonymity and confidentiality to maximize truthfulness.

4 Common Assumptions

The most common assumption for a research study is usually the truthfulness with which participants will respond. However, if the questions asked are of a sensitive nature, it is less plausible to assume honesty than in studies where the questions are more mundane. When participant honesty might be compromised, it should be listed as a limitation of the study rather than an assumption. Assumptions and limitations should never contradict each other. Other common assumptions include how representative a given sample is of the population studied, and the similarity of participants’ characteristics within the study.

• 1 Walden University: Addressing Assumptions

About the Author

Kristina Barroso earned a B.A. in Psychology from Florida International University and works full-time as a classroom teacher in a public school. She teaches middle school English to a wide range of students from struggling readers to advanced and gifted populations. In her spare time, she loves writing articles about education for TheClassroom.com, WorkingMother and other education sites.

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Stating the Obvious: Writing Assumptions, Limitations, and Delimitations

During the process of writing your thesis or dissertation, you might suddenly realize that your research has inherent flaws. Don’t worry! Virtually all projects contain restrictions to your research. However, being able to recognize and accurately describe these problems is the difference between a true researcher and a grade-school kid with a science-fair project. Concerns with truthful responding, access to participants, and survey instruments are just a few of examples of restrictions on your research. In the following sections, the differences among delimitations, limitations, and assumptions of a dissertation will be clarified.

Delimitations

Delimitations are the definitions you set as the boundaries of your own thesis or dissertation, so delimitations are in your control. Delimitations are set so that your goals do not become impossibly large to complete. Examples of delimitations include objectives, research questions, variables, theoretical objectives that you have adopted, and populations chosen as targets to study. When you are stating your delimitations, clearly inform readers why you chose this course of study. The answer might simply be that you were curious about the topic and/or wanted to improve standards of a professional field by revealing certain findings. In any case, you should clearly list the other options available and the reasons why you did not choose these options immediately after you list your delimitations. You might have avoided these options for reasons of practicality, interest, or relativity to the study at hand. For example, you might have only studied Hispanic mothers because they have the highest rate of obese babies. Delimitations are often strongly related to your theory and research questions. If you were researching whether there are different parenting styles between unmarried Asian, Caucasian, African American, and Hispanic women, then a delimitation of your study would be the inclusion of only participants with those demographics and the exclusion of participants from other demographics such as men, married women, and all other ethnicities of single women (inclusion and exclusion criteria). A further delimitation might be that you only included closed-ended Likert scale responses in the survey, rather than including additional open-ended responses, which might make some people more willing to take and complete your survey. Remember that delimitations are not good or bad. They are simply a detailed description of the scope of interest for your study as it relates to the research design. Don’t forget to describe the philosophical framework you used throughout your study, which also delimits your study.

Limitations

Limitations of a dissertation are potential weaknesses in your study that are mostly out of your control, given limited funding, choice of research design, statistical model constraints, or other factors. In addition, a limitation is a restriction on your study that cannot be reasonably dismissed and can affect your design and results. Do not worry about limitations because limitations affect virtually all research projects, as well as most things in life. Even when you are going to your favorite restaurant, you are limited by the menu choices. If you went to a restaurant that had a menu that you were craving, you might not receive the service, price, or location that makes you enjoy your favorite restaurant. If you studied participants’ responses to a survey, you might be limited in your abilities to gain the exact type or geographic scope of participants you wanted. The people whom you managed to get to take your survey may not truly be a random sample, which is also a limitation. If you used a common test for data findings, your results are limited by the reliability of the test. If your study was limited to a certain amount of time, your results are affected by the operations of society during that time period (e.g., economy, social trends). It is important for you to remember that limitations of a dissertation are often not something that can be solved by the researcher. Also, remember that whatever limits you also limits other researchers, whether they are the largest medical research companies or consumer habits corporations. Certain kinds of limitations are often associated with the analytical approach you take in your research, too. For example, some qualitative methods like heuristics or phenomenology do not lend themselves well to replicability. Also, most of the commonly used quantitative statistical models can only determine correlation, but not causation.

Assumptions

Assumptions are things that are accepted as true, or at least plausible, by researchers and peers who will read your dissertation or thesis. In other words, any scholar reading your paper will assume that certain aspects of your study is true given your population, statistical test, research design, or other delimitations. For example, if you tell your friend that your favorite restaurant is an Italian place, your friend will assume that you don’t go there for the sushi. It’s assumed that you go there to eat Italian food. Because most assumptions are not discussed in-text, assumptions that are discussed in-text are discussed in the context of the limitations of your study, which is typically in the discussion section. This is important, because both assumptions and limitations affect the inferences you can draw from your study. One of the more common assumptions made in survey research is the assumption of honesty and truthful responses. However, for certain sensitive questions this assumption may be more difficult to accept, in which case it would be described as a limitation of the study. For example, asking people to report their criminal behavior in a survey may not be as reliable as asking people to report their eating habits. It is important to remember that your limitations and assumptions should not contradict one another. For instance, if you state that generalizability is a limitation of your study given that your sample was limited to one city in the United States, then you should not claim generalizability to the United States population as an assumption of your study. Statistical models in quantitative research designs are accompanied with assumptions as well, some more strict than others. These assumptions generally refer to the characteristics of the data, such as distributions, correlational trends, and variable type, just to name a few. Violating these assumptions can lead to drastically invalid results, though this often depends on sample size and other considerations.

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Search catalog, critical thinking and academic research: assumptions.

• Information
• Point of View
• Assumptions
• Implications

Question Assumptions

An assumption is an unexamined belief: what we think without realizing we think it. Our inferences (also called conclusions) are often based on assumptions that we haven't thought about critically. A critical thinker, however, is attentive to these assumptions because they are sometimes incorrect or misguided. Just because we assume something is true doesn't mean it is.

Think carefully about your assumptions when finding and analyzing information but also think carefully about the assumptions of others. Whether you're looking at a website or a scholarly article, you should always consider the author's assumptions. Are the author's conclusions based on assumptions that she or he hasn't thought about logically?

Critical Questions

• What am I taking for granted?
• Am I assuming something I shouldn't?
• How can I determine whether this assumption is accurate?
• What is this author assuming?
• How can I determine if this author's assumptions are accurate?

Consider the following situations, then respond to these questions:

• Do you agree or disagree with the inference/conclusion? Why or why not?
• What assumption(s) may have led to the inference/conclusion?
• What are some alternative ways of thinking about this situation?

Situation #1

Bill needs six scholarly articles for his paper on the psychological effects of domestic violence. He searches Google for "psychological effects of domestic violence," looks through the first few hits, and finds six sources, including some articles on the websites of legitimate organizations. A few of these articles include bibliographies.

• Bill's Inference/Conclusion: I'm going to stop researching because I have my six sources.

Situation #2

Christie is researching representations of gender in popular music. She decides to search Google and, within a few minutes, locates more sources that she could possibly incorporate into her final paper.

• Christie's Inference/Conclusion: I can just use Google for my research.

Situation #3

Jennifer has decided to write her literary analysis paper on drug use in David Foster Wallace's novel, Infinite Jest (1996). She tries a few Google searches for Infinite Jest, drugs, and drug use, but she has trouble finding scholarly sources. She gives up on Google and moves on to EBSCO Academic Search Premier, one of the databases she heard about in a library instruction class. She runs a search for Infinite Jest and drug use, but she still can't find much.

• Jennifer's Inference/Conclusion: I need to change my topic.
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• Next: Implications >>
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How to make assumptions in a research paper.

In the academic environment, making assumptions is vital as the research statement of the problem when writing a project dissertation. Assumptions in an essay are those statements your audience will take as true or false. Today, we will be looking at making assumptions in research writing and errors to be avoided during this process.

What is assumption?

In academic writing, an assumption is regarded as unexamined belief; that is what we are considering without realizing it. Inarguably all research works conclude based on the assumption that the authors have not critically examined.

The Importance of Assumptions in a Thesis

Deciding what assumptions might arise in your readers’ minds is one of the primary functions to be carried out when writing a research paper. Without a doubt, assumptions are the foundation of any credible and valid research work. In fact, without assumptions, research problems cannot be found as they determine the conclusions that would be gotten from your research work.

Identifying Assumptions

It is essential to point out that the type of assumption will determine the conclusion gotten from the research. For this reason, you should critically consider the kinds of assumptions you make in your research. What then makes a proper assumption? Being able to be verified and justified. To give a reasonable assumption, you must not just state, but explain and cite examples to justify your premise’s validity. On the other hand, a wrong assumption is not easily valid and justified. Take, for instance, in case you are assuming that participants will provide honest answers to questions you ask them, explain how the data was gotten, and steps you will take to ensure their identity is protected to guarantee truthfulness.

Assumptions and Hypotheses: Similarities and differences

Many people tend to mix up an assumption with a hypothesis. Although these two concepts share specific characteristics, they are quite different. Below we list two significant similarities and differences between an assumption and thesis.

Similarities between assumption and thesis:

1. Both assumption and hypothesis can be proved and disapproved during the course of the research.

2. Like thesis an assumption must always be affirmative, never a question.

Differences between an assumption and hypothesis:

1. Unlike an assumption, the researcher consciously works towards proving the validity of the hypothesis used for the research.

2.The research work begins based on an assumption, whereas a theory is a goal the study aims to achieve.

Having differentiated between these two concepts, the question now evolves in many writers’ minds, what then is a premise in research?

Is Premise and Assumption the same?

A premise is commonly described as the assumption that the arguments depend on ”fly.” In essence, we are saying that an assumption is sometimes referred to as a premise of research work. Let’s check out the example below to understand better:

1. All men are mortal;

2. Socrates is a man;

3. Therefore, Socrates is mortal.

From the above example, it is evident that the first two assertions are premises. Why are they assumptions? Because there is no attempt to prove their validity, everyone just accepts them as reality. However, the last statement depends on the first two sentences; if those are untrue, it is also inaccurate and vice versa.

Types of Assumptions

There are two types of Assumptions when writing a research paper: directly stated assumption (explicit) or indirectly stated but implied (Implicitly). So immediately, you pinpoint an assumption in research work, watch out for the two types.

Often, to make an efficient reading, it is necessary to go beyond what has been said, that is, read between the lines.

For example, observe this statement:

Patricia stopped drinking soda The explicit assumption is, “Patricia stopped drinking soda.” The implicit assumption is, “Patricia used to drink soda before.”

Now, see this other example:

Fortunately, Patricia stopped drinking soda

The explicit assumption is, “Patricia stopped drinking soda.” The word “fortunately” indicates that the speaker has a positive opinion of the fact – that is the implicit assumption.

Common Assumptions in Research

Arguably, perhaps the most frequent assumption in any research is around the participants’ sincerity when answering the questions being asked. It is important to note that if the questions you ask the respondents are quite sensitive, it is best to assume plausible honesty when compared to answering impersonal questions. If there is element of subjectivity and compromise in the answer being provided, it should be listed as a limitation of the research, not an assumption. Limitations and assumptions of the study should not be in contrast to each other.

Another widespread assumption is the similarity of participants’ characteristics within the study. Another common assumption in research is determining the level of representation a sample size is for a population.

Four Ways to Deal with Assumptions

Like we earlier mentioned, regardless of the type of research being carried out, assumptions are vital to its success. Despite the critical role it plays in research writing when you re-evaluate the assumptions you have made, sometimes you feel like they are not accurate enough; hence you want to change the assumption. Below we have highlighted four tips on how to deal with assumptions in research writing.

1. Don’t touch them, leave them as they are;

When you see the assumptions, you have made in your research, you may think about leaving them. However, your confidence will be boosted about choosing not to touch them if carefully review them and the options available.

2. Explain them in more detail (make them explicit)

Indeed when you make an assumption, you will likely feel like that is the right thing to do; however, your research work will be more understood if you expound more about the assumption, although you don’t need to give examples to back it up.

3. Offer evidence (convert them into supported claims)

We know at this point; you are worried about the fact that we are asking you to provide evidence. Nevertheless, it is something you should consider if you think your audience will probably not agree with one of the assumptions you have made with an example to back it up. So, in this situation, it is ideal for you to turn your assumption into a claim that has proof.

4. Change them (revise the larger claim)

In certain situations, even you are not convinced by the assumption you are presenting to your audience even after several attempts to prove. In this case, the best thing to do is to review the assumption and the statement it serves as a backbone.

Three Common Mistakes about assumptions

When evaluating an assumption, there are inevitable mistakes to be careful of:

Mistake #1: The assumption is terrible because there is no evidence

Many people make a mistake of saying that when an assumption does not have proof, it will fail. However, if you look at the definition of assumption, you will notice that lack of evidence pops out.

Mistake #2: I can’t entirely agree because we cannot know if it’s true or not

Another common mistake about assumption is that if we cannot know whether it is true or false, we cannot say it is an assumption because there is no room for agreeing or disagreeing. But the reality is that even if we cannot ascertain the assumption, we can make an educated guess and explain the reasons for making the assumption.

Mistake #3: The assumption is reasonable because there is evidence

A lot of people express that when there is proof for an assumption, it is a good one. However, the truth is, when your supposed assumption has evidence, and the author tries to prove it, it is no longer an assumption.

From the above, it is evident that assumption is an integral part of research writing. We believe you can now identify what it is and make assumptions to back up your research.

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5.1 Assumptions underlying research

Learning objectives.

Learners will be able to…

• Ground your research project and working question in the philosophical assumptions of social science
• Define the terms ‘ ontology ‘ and ‘ epistemology ‘ and explain how they relate to quantitative and qualitative research methods

Pre-awareness check (Knowledge)

Thinking back on your practice experience, what types of things were dependent on a person’s own truth and more subjective? What types of things would you consider irrefutable truths and more objective?

Last chapter, we reviewed the ethical commitment that social work researchers have to protect the people and communities impacted by their research. Answering the practical questions of harm, conflicts of interest, and other ethical issues will provide clear foundation of what you can and cannot do as part of your research project. In this chapter, we will transition from the real world to the conceptual world. Together, we will discover and explore the theoretical and philosophical foundations of your project. You should complete this chapter with a better sense of how theoretical and philosophical concepts help you answer your working question, and in turn, how theory and philosophy will affect the research project you design.

Embrace philosophy

The single biggest barrier to engaging with philosophy of science, at least according to some of my students, is the word philosophy. I had one student who told me that as soon as that word came up, she tuned out because she thought it was above her head. As we discussed in Chapter 1, some students already feel like research methods is too complex of a topic, and asking them to engage with philosophical concepts within research is like asking them to tap dance while wearing ice skates.

For those students, I would first answer that this chapter is my favorite one to write because it was the most impactful for me to learn during my MSW program. Finding my theoretical and philosophical home was important for me to develop as a clinician and a researcher. Following our advice in Chapter 2, you’ve hopefully chosen a topic that is important to your interests as a social work practitioner, and consider this chapter an opportunity to find your personal roots in addition to revising your working question and designing your research study.

Exploring theoretical and philosophical questions will cause your working question and research project to become clearer. Consider this chapter as something similar to getting a nice outfit for a fancy occasion. You have to try on a lot of different theories and philosophies before you find the one that fits with what you’re going for. There’s no right way to try on clothes, and there’s no one right theory or philosophy for your project. You might find a good fit with the first one you’ve tried on, or it might take a few different outfits. You have to find ideas that make sense together because they fit with how you think about your topic and how you should study it.

As you read this section, try to think about which assumptions  feel right for your working question and research project. Which assumptions match what you think and believe about your topic? The goal is not to find the “right” answer, but to develop your conceptual understanding of your research topic by finding the right theoretical and philosophical fit.

Theoretical and philosophical fluency

In addition to self-discovery, theoretical and philosophical fluency is a skill that social workers must possess in order to engage in social justice work. That’s because theory and philosophy help sharpen your perceptions of the social world. Just as social workers use empirical data to support their work, they also use theoretical and philosophical foundations. More importantly, theory and philosophy help social workers build heuristics that can help identify the fundamental assumptions at the heart of social conflict and social problems. They alert you to the patterns in the underlying assumptions that different people make and how those assumptions shape their worldview, what they view as true, and what they hope to accomplish. In the next section, we will review feminist and other critical perspectives on research, and they should help inform you of how assumptions about research can reinforce existing oppression.

Understanding these deeper structures is a true gift of social work research. Because we acknowledge the usefulness and truth value of multiple philosophies and worldviews contained in this chapter, we can arrive at a deeper and more nuanced understanding of the social world. Methods can be closely associated with particular worldviews or ideologies. There are necessarily philosophical and theoretical aspects to this, and this can be intimidating at times, but it’s important to critically engage with these questions to improve the quality of research.

Building your ice float

Although it may not seem like it right now, your project will develop a from a strong connection to previous theoretical and philosophical ideas about your topic. It’s likely you already have some (perhaps unstated) philosophical or theoretical ideas that undergird your thinking on the topic. Moreover, the philosophical questions we review here should inform how you understand different theories and practice modalities in social work, as they deal with the bedrock questions about science and human knowledge.

Before we can dive into philosophy, we need to recall our conversation from Chapter 1 about objective truth and subjective truths. Let’s test your knowledge with a quick example. Is crime on the rise in the United States? A recent Five Thirty Eight article highlights the disparity between historical trends on crime that are at or near their lowest in the thirty years with broad perceptions by the public that crime is on the rise (Koerth & Thomson-DeVeaux, 2020). [1] Social workers skilled at research can marshal objective facts, much like the authors do, to demonstrate that people’s perceptions are not based on a rational interpretation of the world. Of course, that is not where our work ends. Subjective facts might seek to decenter this narrative of ever-increasing crime, deconstruct is racist and oppressive origins, or simply document how that narrative shapes how individuals and communities conceptualize their world.

Objective does not mean right, and subjective does not mean wrong. Researchers must understand what kind of truth they are searching for so they can choose a theory(ies), develop a theoretical framework (in quantitative research), select an appropriate methodology, and make sure the research question(s) matches them all. As we discussed in Chapter 1, researchers seeking objective truth (one of the philosophical foundations at the bottom of Figure 5.1) often employ quantitative methods (one of the methods at the top of Figure 5.1). Similarly, researchers seeking subjective truths (again, at the bottom of Figure 5.1) often employ qualitative methods (at the top of Figure 5.1). This chapter is about the connective tissue, and by the time you are done reading, you should have a first draft of a theoretical and philosophical (a.k.a. paradigmatic) framework for your study.

Ontology: Assumptions about what is real and true

In section 1.2, we reviewed the two types of truth that social work researchers seek— objective truth and subjective truths —and linked these with the methods—quantitative and qualitative—that researchers use to study the world. If those ideas aren’t fresh in your mind, you may want to navigate back to that section for an introduction.

These two types of truth rely on different assumptions about what is real in the social world—i.e., they have a different ontology . Ontology refers to the study of being (literally, it means “rational discourse about being”). In philosophy, basic questions about existence are typically posed as ontological, e.g.:

• What is there?
• What types of things are there?
• How can we describe existence?
• What kind of categories can things go into?
• Are the categories of existence hierarchical?

Objective vs. subjective ontologies

At first, it may seem silly to question whether the phenomena we encounter in the social world are real. Of course you exist, your thoughts exist, your computer exists, and your friends exist. You can see them with your eyes. This is the ontological framework of  realism , which simply means that the concepts we talk about in science exist independent of observation (Burrell & Morgan, 1979). [2] Obviously, when we close our eyes, the universe does not disappear. You may be familiar with the philosophical conundrum: “If a tree falls in a forest and no one is around to hear it, does it make a sound?”

The natural sciences, like physics and biology, also generally rely on the assumption of realism. Lone trees falling make a sound. We assume that gravity and the rest of physics are there, even when no one is there to observe them. Mitochondria are easy to spot with a powerful microscope, and we can observe and theorize about their function in a cell. The gravitational force is invisible, but clearly apparent from observable facts, such as watching an apple fall from a tree. Of course, our theories about gravity have changed over the years. Improvements were made when observations could not be correctly explained using existing theories and new theories emerged that provided a better explanation of the data.

As we discussed in section 1.2, culture-bound syndromes are an excellent example of where you might come to question realism. Of course, from a Western perspective as researchers in the United States, we think that the Diagnostic and Statistical Manual (DSM) classification of mental health disorders is real and that these culture-bound syndromes are aberrations from the norm. But what about if you were a person from Korea experiencing Hwabyeong? Wouldn’t you consider the Western diagnosis of somatization disorder to be incorrect or incomplete? This conflict raises the question–do either Hwabyeong   or DSM diagnoses like post-traumatic stress disorder (PTSD) really exist at all…or are they just social constructs that only exist in our minds?

If your answer is “no, they do not exist,” you are adopting the ontology of anti-realism ( or relativism ), or the idea that social concepts do not exist outside of human thought. Unlike the realists who seek a single, universal truth, the anti-realists perceive a sea of truths, created and shared within a social and cultural context. Unlike objective truth, which is true for all, subjective truths will vary based on who you are observing and the context in which you are observing them. The beliefs, opinions, and preferences of people are actually truths that social scientists measure and describe. Additionally, subjective truths do not exist independent of human observation because they are the product of the human mind. We negotiate what is true in the social world through language, arriving at a consensus and engaging in debate within our socio-cultural context.

These theoretical assumptions should sound familiar if you’ve studied social constructivism or symbolic interactionism in MSW courses, most likely in human behavior in the social environment (HBSE). [3] From an anti-realist perspective, what distinguishes the social sciences from natural sciences is human thought. When we try to conceptualize trauma from an anti-realist perspective, we must pay attention to the feelings, opinions, and stories in people’s minds. In their most radical formulations, anti-realists propose that these feelings and stories are all that truly exist.

What happens when a situation is incorrectly interpreted? Certainly, who is correct about what is a bit subjective. It depends on who you ask. Even if you can determine whether a person is actually incorrect, they think they are right. Thus, what may not be objectively true for everyone is nevertheless true to the individual interpreting the situation. Furthermore, they act on the assumption that they are right. We all do. Much of our behaviors and interactions are a manifestation of our personal subjective truth. In this sense, even incorrect interpretations are truths, even though they are true only to one person or a group of misinformed people. This leads us to question whether the social concepts we think about really exist. For researchers using subjective ontologies, they might only exist in our minds; whereas, researchers who use objective ontologies which assume these concepts exist independent of thought.

How do we resolve this dichotomy? As social workers, we know that often times what appears to be an either/or situation is actually a both/and situation. Let’s take the example of trauma. There is clearly an objective thing called trauma. We can draw out objective facts about trauma and how it interacts with other concepts in the social world such as family relationships and mental health. However, that understanding is always bound within a specific cultural and historical context. Moreover, each person’s individual experience and conceptualization of trauma is also true. Much like a client who tells you their truth through their stories and reflections, when a participant in a research study tells you what their trauma means to them, it is real even though only they experience and know it that way. By using both objective and subjective analytic lenses, we can explore different aspects of trauma—what it means to everyone, always, everywhere, and what is means to one person or group of people, in a specific place and time.

Epistemology: Assumptions about how we know things

Having discussed what is true, we can proceed to the next natural question—how can we come to know what is real and true? This is epistemology . Epistemology is derived from the Ancient Greek epistēmē which refers to systematic or reliable knowledge (as opposed to doxa, or “belief”). Basically, it means “rational discourse about knowledge,” and the focus is the study of knowledge and methods used to generate knowledge. Epistemology has a history as long as philosophy, and lies at the foundation of both scientific and philosophical knowledge.

Epistemological questions include:

• What is knowledge?
• How can we claim to know anything at all?
• What does it mean to know something?
• What makes a belief justified?
• What is the relationship between the knower and what can be known?

While these philosophical questions can seem far removed from real-world interaction, thinking about these kinds of questions in the context of research helps you target your inquiry by informing your methods and helping you revise your working question. Epistemology is closely connected to method as they are both concerned with how to create and validate knowledge. Research methods are essentially epistemologies – by following a certain process we support our claim to know about the things we have been researching. Inappropriate or poorly followed methods can undermine claims to have produced new knowledge or discovered a new truth. This can have implications for future studies that build on the data and/or conceptual framework used.

Research methods can be thought of as essentially stripped down, purpose-specific epistemologies. The knowledge claims that underlie the results of surveys, focus groups, and other common research designs ultimately rest on epistemological assumptions of their methods. Focus groups and other qualitative methods usually rely on subjective epistemological (and ontological) assumptions. Surveys and other quantitative methods usually rely on objective epistemological assumptions. These epistemological assumptions often entail congruent subjective or objective ontological assumptions about the ultimate questions about reality.

Objective vs. subjective epistemologies

One key consideration here is the status of ‘truth’ within a particular epistemology or research method. If, for instance, some approaches emphasize subjective knowledge and deny the possibility of an objective truth, what does this mean for choosing a research method?

We began to answer this question in Chapter 1 when we described the scientific method and objective and subjective truths. Epistemological subjectivism focuses on what people think and feel about a situation, while epistemological objectivism focuses on objective facts irrelevant to our interpretation of a situation (Lin, 2015). [4]

While there are many important questions about epistemology to ask (e.g., “How can I be sure of what I know?” or “What can I not know?” see Willis, 2007 [5] for more), from a pragmatic perspective most relevant epistemological question in the social sciences is whether truth is better accessed using numerical data or words and performances. Generally, scientists approaching research with an objective epistemology (and realist ontology) will use quantitative methods to arrive at scientific truth. Quantitative methods examine numerical data to precisely describe and predict elements of the social world. For example, while people can have different definitions for poverty, an objective measurement such as an annual income of “less than $25,100 for a family of four” provides a precise measurement that can be compared to incomes from all other people in any society from any time period, and refers to real quantities of money that exist in the world. Mathematical relationships are uniquely useful in that they allow comparisons across individuals as well as time and space. In this book, we will review the most common designs used in quantitative research: surveys and experiments. These types of studies usually rely on the epistemological assumption that mathematics can represent the phenomena and relationships we observe in the social world.

Although mathematical relationships are useful, they are limited in what they can tell you. While you can use quantitative methods to measure individuals’ experiences and thought processes, you will miss the story behind the numbers. To analyze stories scientifically, we need to examine their expression in interviews, journal entries, performances, and other cultural artifacts using qualitative methods . Because social science studies human interaction and the reality we all create and share in our heads, subjectivists focus on language and other ways we communicate our inner experience. Qualitative methods allow us to scientifically investigate language and other forms of expression—to pursue research questions that explore the words people write and speak. This is consistent with epistemological subjectivism’s focus on individual and shared experiences, interpretations, and stories.

It is important to note that qualitative methods are entirely compatible with seeking objective truth. Approaching qualitative analysis with a more objective perspective, we look simply at what was said and examine its surface-level meaning. If a person says they brought their kids to school that day, then that is what is true. A researcher seeking subjective truth may focus on how the person says the words—their tone of voice, facial expressions, metaphors, and so forth. By focusing on these things, the researcher can understand what it meant to the person to say they dropped their kids off at school. Perhaps in describing dropping their children off at school, the person thought of their parents doing the same thing. In this way, subjective truths are deeper, more personalized, and difficult to generalize.

Putting it all together

As you might guess by the structure of the next two parts of this textbook, the distinction between quantitative and qualitative is important. Because of the distinct philosophical assumptions of objectivity and subjectivity, it will inform how you define the concepts in your research question, how you measure them, and how you gather and interpret your raw data. You certainly do not need to have a final answer right now! But stop for a minute and think about which approach feels right so far. In the next section, we will consider another set of philosophical assumptions that relate to ethics and the role of research in achieving social justice.

Key Takeaways

• Philosophers of science disagree on the basic tenets of what is true and how we come to know what is true.
• Researchers searching for objective truth will likely have a different research design, and methods than researchers searching for subjective truths.
• These differences are due to different assumptions about what is real and true (ontology) and how we can come to understand what is real and true (epistemology).

TRACK 1 (IF YOU ARE CREATING A RESEARCH PROPOSAL FOR THIS CLASS):

Does an objective or subjective epistemological/ontological framework make the most sense for your research project?

• Are you more concerned with how people think and feel about your topic, their subjective truths—more specific to the time and place of your project?
• Or are you more concerned with objective truth, so that your results might generalize to populations beyond the ones in your study?

Using your answer to the above question, describe how either quantitative or qualitative methods make the most sense for your project.

TRACK 2 (IF YOU AREN’T CREATING A RESEARCH PROPOSAL FOR THIS CLASS):

You are interested in researching bullying among school-aged children, and how this impacts students’ academic success.

• If you are using an objective epistemological/ontological framework, what types of research questions might you ask?
• If you are using a subjective epistemological/ontological framework, what types of research questions might you ask?
• Koerth, M. & Thomson-DeVeaux, A. (2020, August 3). Many Americans are convinced crime is rising in the U.S. They're wrong. FiveThirtyEight . Retrieved from: https://fivethirtyeight.com/features/many-americans-are-convinced-crime-is-rising-in-the-u-s-theyre-wrong ↵
• Burrell, G. & Morgan, G. (1979). Sociological paradigms and organizational analysis . Routledge. ↵
• Here are links to two HBSE open textbooks, if you are unfamiliar with social work theories. https://uark.pressbooks.pub/hbse1/ and https://uark.pressbooks.pub/humanbehaviorandthesocialenvironment2/ ↵
• Lin, C. T. (2016). A critique of epistemic subjectivity. Philosophia, 44 (3), 915-920. ↵
• Wills, J. W. (2007).  World views, paradigms and the practice of social science research. Thousand Oaks, CA: Sage. ↵

a single truth, observed without bias, that is universally applicable

one truth among many, bound within a social and cultural context

assumptions about what is real and true

assumptions about how we come to know what is real and true

quantitative methods examine numerical data to precisely describe and predict elements of the social world

qualitative methods interpret language and behavior to understand the world from the perspectives of other people

Doctoral Research Methods in Social Work Copyright © by Mavs Open Press. All Rights Reserved.

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The Craft of Writing a Strong Hypothesis

Table of Contents

Writing a hypothesis is one of the essential elements of a scientific research paper. It needs to be to the point, clearly communicating what your research is trying to accomplish. A blurry, drawn-out, or complexly-structured hypothesis can confuse your readers. Or worse, the editor and peer reviewers.

A captivating hypothesis is not too intricate. This blog will take you through the process so that, by the end of it, you have a better idea of how to convey your research paper's intent in just one sentence.

What is a Hypothesis?

The first step in your scientific endeavor, a hypothesis, is a strong, concise statement that forms the basis of your research. It is not the same as a thesis statement , which is a brief summary of your research paper .

The sole purpose of a hypothesis is to predict your paper's findings, data, and conclusion. It comes from a place of curiosity and intuition . When you write a hypothesis, you're essentially making an educated guess based on scientific prejudices and evidence, which is further proven or disproven through the scientific method.

The reason for undertaking research is to observe a specific phenomenon. A hypothesis, therefore, lays out what the said phenomenon is. And it does so through two variables, an independent and dependent variable.

The independent variable is the cause behind the observation, while the dependent variable is the effect of the cause. A good example of this is “mixing red and blue forms purple.” In this hypothesis, mixing red and blue is the independent variable as you're combining the two colors at your own will. The formation of purple is the dependent variable as, in this case, it is conditional to the independent variable.

Different Types of Hypotheses‌

Types of hypotheses

Some would stand by the notion that there are only two types of hypotheses: a Null hypothesis and an Alternative hypothesis. While that may have some truth to it, it would be better to fully distinguish the most common forms as these terms come up so often, which might leave you out of context.

Apart from Null and Alternative, there are Complex, Simple, Directional, Non-Directional, Statistical, and Associative and casual hypotheses. They don't necessarily have to be exclusive, as one hypothesis can tick many boxes, but knowing the distinctions between them will make it easier for you to construct your own.

1. Null hypothesis

A null hypothesis proposes no relationship between two variables. Denoted by H 0 , it is a negative statement like “Attending physiotherapy sessions does not affect athletes' on-field performance.” Here, the author claims physiotherapy sessions have no effect on on-field performances. Even if there is, it's only a coincidence.

2. Alternative hypothesis

Considered to be the opposite of a null hypothesis, an alternative hypothesis is donated as H1 or Ha. It explicitly states that the dependent variable affects the independent variable. A good  alternative hypothesis example is “Attending physiotherapy sessions improves athletes' on-field performance.” or “Water evaporates at 100 °C. ” The alternative hypothesis further branches into directional and non-directional.

• Directional hypothesis: A hypothesis that states the result would be either positive or negative is called directional hypothesis. It accompanies H1 with either the ‘<' or ‘>' sign.
• Non-directional hypothesis: A non-directional hypothesis only claims an effect on the dependent variable. It does not clarify whether the result would be positive or negative. The sign for a non-directional hypothesis is ‘≠.'

3. Simple hypothesis

A simple hypothesis is a statement made to reflect the relation between exactly two variables. One independent and one dependent. Consider the example, “Smoking is a prominent cause of lung cancer." The dependent variable, lung cancer, is dependent on the independent variable, smoking.

4. Complex hypothesis

In contrast to a simple hypothesis, a complex hypothesis implies the relationship between multiple independent and dependent variables. For instance, “Individuals who eat more fruits tend to have higher immunity, lesser cholesterol, and high metabolism.” The independent variable is eating more fruits, while the dependent variables are higher immunity, lesser cholesterol, and high metabolism.

5. Associative and casual hypothesis

Associative and casual hypotheses don't exhibit how many variables there will be. They define the relationship between the variables. In an associative hypothesis, changing any one variable, dependent or independent, affects others. In a casual hypothesis, the independent variable directly affects the dependent.

6. Empirical hypothesis

Also referred to as the working hypothesis, an empirical hypothesis claims a theory's validation via experiments and observation. This way, the statement appears justifiable and different from a wild guess.

Say, the hypothesis is “Women who take iron tablets face a lesser risk of anemia than those who take vitamin B12.” This is an example of an empirical hypothesis where the researcher  the statement after assessing a group of women who take iron tablets and charting the findings.

7. Statistical hypothesis

The point of a statistical hypothesis is to test an already existing hypothesis by studying a population sample. Hypothesis like “44% of the Indian population belong in the age group of 22-27.” leverage evidence to prove or disprove a particular statement.

Characteristics of a Good Hypothesis

Writing a hypothesis is essential as it can make or break your research for you. That includes your chances of getting published in a journal. So when you're designing one, keep an eye out for these pointers:

• A research hypothesis has to be simple yet clear to look justifiable enough.
• It has to be testable — your research would be rendered pointless if too far-fetched into reality or limited by technology.
• It has to be precise about the results —what you are trying to do and achieve through it should come out in your hypothesis.
• A research hypothesis should be self-explanatory, leaving no doubt in the reader's mind.
• If you are developing a relational hypothesis, you need to include the variables and establish an appropriate relationship among them.
• A hypothesis must keep and reflect the scope for further investigations and experiments.

Separating a Hypothesis from a Prediction

Outside of academia, hypothesis and prediction are often used interchangeably. In research writing, this is not only confusing but also incorrect. And although a hypothesis and prediction are guesses at their core, there are many differences between them.

A hypothesis is an educated guess or even a testable prediction validated through research. It aims to analyze the gathered evidence and facts to define a relationship between variables and put forth a logical explanation behind the nature of events.

Predictions are assumptions or expected outcomes made without any backing evidence. They are more fictionally inclined regardless of where they originate from.

For this reason, a hypothesis holds much more weight than a prediction. It sticks to the scientific method rather than pure guesswork. "Planets revolve around the Sun." is an example of a hypothesis as it is previous knowledge and observed trends. Additionally, we can test it through the scientific method.

Whereas "COVID-19 will be eradicated by 2030." is a prediction. Even though it results from past trends, we can't prove or disprove it. So, the only way this gets validated is to wait and watch if COVID-19 cases end by 2030.

Finally, How to Write a Hypothesis

Quick tips on writing a hypothesis

1.  Be clear about your research question

A hypothesis should instantly address the research question or the problem statement. To do so, you need to ask a question. Understand the constraints of your undertaken research topic and then formulate a simple and topic-centric problem. Only after that can you develop a hypothesis and further test for evidence.

2. Carry out a recce

Once you have your research's foundation laid out, it would be best to conduct preliminary research. Go through previous theories, academic papers, data, and experiments before you start curating your research hypothesis. It will give you an idea of your hypothesis's viability or originality.

Making use of references from relevant research papers helps draft a good research hypothesis. SciSpace Discover offers a repository of over 270 million research papers to browse through and gain a deeper understanding of related studies on a particular topic. Additionally, you can use SciSpace Copilot , your AI research assistant, for reading any lengthy research paper and getting a more summarized context of it. A hypothesis can be formed after evaluating many such summarized research papers. Copilot also offers explanations for theories and equations, explains paper in simplified version, allows you to highlight any text in the paper or clip math equations and tables and provides a deeper, clear understanding of what is being said. This can improve the hypothesis by helping you identify potential research gaps.

3. Create a 3-dimensional hypothesis

Variables are an essential part of any reasonable hypothesis. So, identify your independent and dependent variable(s) and form a correlation between them. The ideal way to do this is to write the hypothetical assumption in the ‘if-then' form. If you use this form, make sure that you state the predefined relationship between the variables.

In another way, you can choose to present your hypothesis as a comparison between two variables. Here, you must specify the difference you expect to observe in the results.

4. Write the first draft

Now that everything is in place, it's time to write your hypothesis. For starters, create the first draft. In this version, write what you expect to find from your research.

Clearly separate your independent and dependent variables and the link between them. Don't fixate on syntax at this stage. The goal is to ensure your hypothesis addresses the issue.

5. Proof your hypothesis

After preparing the first draft of your hypothesis, you need to inspect it thoroughly. It should tick all the boxes, like being concise, straightforward, relevant, and accurate. Your final hypothesis has to be well-structured as well.

Research projects are an exciting and crucial part of being a scholar. And once you have your research question, you need a great hypothesis to begin conducting research. Thus, knowing how to write a hypothesis is very important.

Now that you have a firmer grasp on what a good hypothesis constitutes, the different kinds there are, and what process to follow, you will find it much easier to write your hypothesis, which ultimately helps your research.

Now it's easier than ever to streamline your research workflow with SciSpace Discover . Its integrated, comprehensive end-to-end platform for research allows scholars to easily discover, write and publish their research and fosters collaboration.

It includes everything you need, including a repository of over 270 million research papers across disciplines, SEO-optimized summaries and public profiles to show your expertise and experience.

If you found these tips on writing a research hypothesis useful, head over to our blog on Statistical Hypothesis Testing to learn about the top researchers, papers, and institutions in this domain.

Frequently Asked Questions (FAQs)

1. what is the definition of hypothesis.

According to the Oxford dictionary, a hypothesis is defined as “An idea or explanation of something that is based on a few known facts, but that has not yet been proved to be true or correct”.

2. What is an example of hypothesis?

The hypothesis is a statement that proposes a relationship between two or more variables. An example: "If we increase the number of new users who join our platform by 25%, then we will see an increase in revenue."

3. What is an example of null hypothesis?

A null hypothesis is a statement that there is no relationship between two variables. The null hypothesis is written as H0. The null hypothesis states that there is no effect. For example, if you're studying whether or not a particular type of exercise increases strength, your null hypothesis will be "there is no difference in strength between people who exercise and people who don't."

4. What are the types of research?

• Fundamental research

• Applied research

• Qualitative research

• Quantitative research

• Mixed research

• Exploratory research

• Longitudinal research

• Cross-sectional research

• Field research

• Laboratory research

• Fixed research

• Flexible research

• Action research

• Policy research

• Classification research

• Comparative research

• Causal research

• Inductive research

• Deductive research

5. How to write a hypothesis?

• Your hypothesis should be able to predict the relationship and outcome.

• Avoid wordiness by keeping it simple and brief.

• Your hypothesis should contain observable and testable outcomes.

• Your hypothesis should be relevant to the research question.

6. What are the 2 types of hypothesis?

• Null hypotheses are used to test the claim that "there is no difference between two groups of data".

• Alternative hypotheses test the claim that "there is a difference between two data groups".

7. Difference between research question and research hypothesis?

A research question is a broad, open-ended question you will try to answer through your research. A hypothesis is a statement based on prior research or theory that you expect to be true due to your study. Example - Research question: What are the factors that influence the adoption of the new technology? Research hypothesis: There is a positive relationship between age, education and income level with the adoption of the new technology.

8. What is plural for hypothesis?

The plural of hypothesis is hypotheses. Here's an example of how it would be used in a statement, "Numerous well-considered hypotheses are presented in this part, and they are supported by tables and figures that are well-illustrated."

9. What is the red queen hypothesis?

The red queen hypothesis in evolutionary biology states that species must constantly evolve to avoid extinction because if they don't, they will be outcompeted by other species that are evolving. Leigh Van Valen first proposed it in 1973; since then, it has been tested and substantiated many times.

10. Who is known as the father of null hypothesis?

The father of the null hypothesis is Sir Ronald Fisher. He published a paper in 1925 that introduced the concept of null hypothesis testing, and he was also the first to use the term itself.

11. When to reject null hypothesis?

You need to find a significant difference between your two populations to reject the null hypothesis. You can determine that by running statistical tests such as an independent sample t-test or a dependent sample t-test. You should reject the null hypothesis if the p-value is less than 0.05.

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Types of Essays in Academic Writing - Quick Guide (2024)

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Writing a Paper: Addressing Assumptions

Addressing assumptions.

One of the first decisions writers have to make is to decide on the reader’s knowledge base. Will the reader know what I mean by X, or do I need to define it? Will the reader have a different definition of X than I do? Will the reader agree that X is important, or do I need to justify my study of X?

These kinds of decisions will vary by case, but there are some general guidelines. When deciding what you can assume about the knowledge you might share with your reader, ask yourself these questions:

• Do the journals in my field share a common definition of this concept? For instance, if you plan to discuss a certain trend in your field, can you assume that your colleagues will be familiar with that trend and the language you are using to describe it? A quick review of current journals in your field should help you determine the common practice.
• Could this term or topic be understood differently by different readers? For instance, buzzwords like at-risk and burnout appear in many Walden papers, often with very different implications and contexts. If you plan to use a term that may have different interpretations, be sure to define it clearly for the purposes of your paper.
• Is this an idea that is particularly present in my own environment? Sometimes, writers assume that a reader will be familiar with an idea because it is so prevalent in their own setting. The problem, of course, is that every workplace or region is different, and what may be a pressing issue in one place isn’t even on the radar somewhere else.
• Am I assuming that the reader already believes in the importance of this issue? When writers have a passion for solving a certain problem, they often forget to clarify why it is a problem. Remember that while your reader may share some of your knowledge base, he or she might not share your perspective. Any time you find yourself beginning a sentence with “We all know that ___ is a problem,” you’ll want to stop and examine that assumption.
• Is the term or idea part of current debate and practice? A notion can occupy many people’s minds for a while and then fall out of fashion in favor of a newer idea. When writing, make sure that your vocabulary is current, reflecting changes in thinking that may have occurred very recently.

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Understanding Science

How science REALLY works...

• Understanding Science 101
• All scientific tests involve making assumptions.
• These assumptions can be independently tested, increasing our confidence in our test results.

Making assumptions

Much as we might like to avoid it, all scientific tests involve making assumptions — many of them justified. For example, imagine a very simple test of the hypothesis that substance A stops bacterial growth. Some Petri dishes are spread with a mixture of substance A and bacterial growth medium, and others are spread with a mixture of inert substance B and bacterial growth medium. Bacteria are spread on all the Petri dishes, and one day later, the plates are examined to see which fostered the growth of bacterial colonies and which did not. This test is straightforward, but still relies on many assumptions: we assume that the bacteria can grow on the growth medium, we assume that substance B does not affect bacterial growth, we assume that one day is long enough for colonies to grow, and we assume that the color pen we use to mark the outside of the dishes is not influencing bacterial growth.

Technically, these are all assumptions, but they are perfectly reasonable ones that can be tested. The scientist performing the experiment described above would justify many of her assumptions by performing additional tests in parallel with the experimental ones. For example, she would separately test whether substance B affects bacterial growth to check that it was indeed inert as she’d assumed. Other assumptions are justified by past tests performed by other scientists. For instance, the question of whether or not bacteria can grow on the growth medium would have been studied by many previous researchers. And some assumptions might remain untested simply because all of our knowledge about the field suggests that the assumption is a safe one (e.g., we know of no reason why bacteria should multiply faster when their dishes are marked with a red, rather than a green, pen). All tests involve assumptions, but most of these are assumptions that can and have been verified separately.

Nevertheless, when evaluating an idea in light of test results, it’s important to keep in mind the test’s assumptions and how well-supported they are. If an expectation generated by an idea is not borne out in a test, it might be because the idea is wrong and should be rejected, or it might be that the idea is right, but an assumption of the test has been violated. And if the test results end up lending support to the idea, it might be because the idea is correct and should be accepted , or it might be because a violated assumption has produced a false positive result.

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Very complex hypotheses — for example, regarding the Earth’s atmosphere — sometimes rely on many sub-hypotheses, or assumptions. To see an example of how changes in these assumptions can affect the over-arching hypothesis, check out the story  Ozone depletion: Uncovering the hidden hazard of hairspray .

• All the assumptions that are part of a particular test are also, in a sense, hypotheses — ideas about how something works that could be correct or incorrect. How does science investigate any single hypothesis if they always get bundled together in our tests? To find out, visit  Bundle up your hypotheses .
• All of science is based on a few fundamental assumptions that transcend any individual experiment or study. To learn what these are, visit  Basic assumptions of science .

Competing ideas: Other considerations

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How to Write Limitations of the Study (with examples)

This blog emphasizes the importance of recognizing and effectively writing about limitations in research. It discusses the types of limitations, their significance, and provides guidelines for writing about them, highlighting their role in advancing scholarly research.

Updated on August 24, 2023

No matter how well thought out, every research endeavor encounters challenges. There is simply no way to predict all possible variances throughout the process.

These uncharted boundaries and abrupt constraints are known as limitations in research . Identifying and acknowledging limitations is crucial for conducting rigorous studies. Limitations provide context and shed light on gaps in the prevailing inquiry and literature.

This article explores the importance of recognizing limitations and discusses how to write them effectively. By interpreting limitations in research and considering prevalent examples, we aim to reframe the perception from shameful mistakes to respectable revelations.

What are limitations in research?

In the clearest terms, research limitations are the practical or theoretical shortcomings of a study that are often outside of the researcher’s control . While these weaknesses limit the generalizability of a study’s conclusions, they also present a foundation for future research.

Sometimes limitations arise from tangible circumstances like time and funding constraints, or equipment and participant availability. Other times the rationale is more obscure and buried within the research design. Common types of limitations and their ramifications include:

• Theoretical: limits the scope, depth, or applicability of a study.
• Methodological: limits the quality, quantity, or diversity of the data.
• Empirical: limits the representativeness, validity, or reliability of the data.
• Analytical: limits the accuracy, completeness, or significance of the findings.
• Ethical: limits the access, consent, or confidentiality of the data.

Regardless of how, when, or why they arise, limitations are a natural part of the research process and should never be ignored . Like all other aspects, they are vital in their own purpose.

Why is identifying limitations important?

Whether to seek acceptance or avoid struggle, humans often instinctively hide flaws and mistakes. Merging this thought process into research by attempting to hide limitations, however, is a bad idea. It has the potential to negate the validity of outcomes and damage the reputation of scholars.

By identifying and addressing limitations throughout a project, researchers strengthen their arguments and curtail the chance of peer censure based on overlooked mistakes. Pointing out these flaws shows an understanding of variable limits and a scrupulous research process.

Showing awareness of and taking responsibility for a project’s boundaries and challenges validates the integrity and transparency of a researcher. It further demonstrates the researchers understand the applicable literature and have thoroughly evaluated their chosen research methods.

Presenting limitations also benefits the readers by providing context for research findings. It guides them to interpret the project’s conclusions only within the scope of very specific conditions. By allowing for an appropriate generalization of the findings that is accurately confined by research boundaries and is not too broad, limitations boost a study’s credibility .

Limitations are true assets to the research process. They highlight opportunities for future research. When researchers identify the limitations of their particular approach to a study question, they enable precise transferability and improve chances for reproducibility. 

Simply stating a project’s limitations is not adequate for spurring further research, though. To spark the interest of other researchers, these acknowledgements must come with thorough explanations regarding how the limitations affected the current study and how they can potentially be overcome with amended methods.

How to write limitations

Typically, the information about a study’s limitations is situated either at the beginning of the discussion section to provide context for readers or at the conclusion of the discussion section to acknowledge the need for further research. However, it varies depending upon the target journal or publication guidelines. 

Don’t hide your limitations

It is also important to not bury a limitation in the body of the paper unless it has a unique connection to a topic in that section. If so, it needs to be reiterated with the other limitations or at the conclusion of the discussion section. Wherever it is included in the manuscript, ensure that the limitations section is prominently positioned and clearly introduced.

While maintaining transparency by disclosing limitations means taking a comprehensive approach, it is not necessary to discuss everything that could have potentially gone wrong during the research study. If there is no commitment to investigation in the introduction, it is unnecessary to consider the issue a limitation to the research. Wholly consider the term ‘limitations’ and ask, “Did it significantly change or limit the possible outcomes?” Then, qualify the occurrence as either a limitation to include in the current manuscript or as an idea to note for other projects. 

Writing limitations

Once the limitations are concretely identified and it is decided where they will be included in the paper, researchers are ready for the writing task. Including only what is pertinent, keeping explanations detailed but concise, and employing the following guidelines is key for crafting valuable limitations:

1) Identify and describe the limitations : Clearly introduce the limitation by classifying its form and specifying its origin. For example:

• An unintentional bias encountered during data collection
• An intentional use of unplanned post-hoc data analysis

2) Explain the implications : Describe how the limitation potentially influences the study’s findings and how the validity and generalizability are subsequently impacted. Provide examples and evidence to support claims of the limitations’ effects without making excuses or exaggerating their impact. Overall, be transparent and objective in presenting the limitations, without undermining the significance of the research. 

3) Provide alternative approaches for future studies : Offer specific suggestions for potential improvements or avenues for further investigation. Demonstrate a proactive approach by encouraging future research that addresses the identified gaps and, therefore, expands the knowledge base.

Whether presenting limitations as an individual section within the manuscript or as a subtopic in the discussion area, authors should use clear headings and straightforward language to facilitate readability. There is no need to complicate limitations with jargon, computations, or complex datasets.

Examples of common limitations

Limitations are generally grouped into two categories , methodology and research process .

Methodology limitations

Methodology may include limitations due to:

• Sample size
• Lack of available or reliable data
• Lack of prior research studies on the topic
• Measure used to collect the data
• Self-reported data

The researcher is addressing how the large sample size requires a reassessment of the measures used to collect and analyze the data.

Research process limitations

Limitations during the research process may arise from:

• Access to information
• Longitudinal effects
• Cultural and other biases
• Language fluency
• Time constraints

The author is pointing out that the model’s estimates are based on potentially biased observational studies.

Final thoughts

Successfully proving theories and touting great achievements are only two very narrow goals of scholarly research. The true passion and greatest efforts of researchers comes more in the form of confronting assumptions and exploring the obscure.

In many ways, recognizing and sharing the limitations of a research study both allows for and encourages this type of discovery that continuously pushes research forward. By using limitations to provide a transparent account of the project's boundaries and to contextualize the findings, researchers pave the way for even more robust and impactful research in the future.

Charla Viera, MS

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Assumptions, Making Recommendations, and Dissemination

This section challenges assumptions, explores making intervention recommendations, and dissemination of findings.

Content includes:

• Assumptions
• Making recommendations

Dissemination

Objectives:

• List two assumptions related to an evidence-based project.
• Check assumptions related to an evidence-based project.
• Describe recommended interventions for an EBP project.

As we move forward with creating your EBP Poster, you will need to really evaluate your own assumptions. As a beginning nursing student, it is fairly reasonable and expected to insert one’s own experiences and assumptions into the published research. It’s easy to “not” see results objectively. This is where the phrase, “Never make assumptions without seeking clarification” comes into play.

What are assumptions? Assumptions   are statements or perceptions thought to be true and taken for granted; a thing that is accepted to be true or certain. Assumptions are ingrained in thinking and are strongly impacted by one’s unique personality and culture. Assumptions are the often used as the basic for thinking. People tend to create assumptions into habits of thinking and doing (Brookfield, 1987). By asking and answering questions, one can develop skills in uncovering assumptions (Paul & Elder, 2008).

Strive to become aware of your assumptions and integrate this cognitive skill into your daily life. This will help you to prevent thinking errors. The act of making assumptions is a good thing, as this is the basis for thinking. However, some assumptions are incorrect, so critical thinkers develop the skill of checking their assumptions. In this module, the meaning of an assumption, how to check assumptions, and how assumptions relate to evidence-based practice is the primary focus. Since assumptions are so ingrained in people, part of being a critical thinker is to practice assumption awareness.

Remember, we would not walk into a room, look at a flat line on a monitor, and simply assume the patient is dead, right? We would assess the situation – airway, breathing, circulation, and so on. In doing so, we are seeking clarification. We are asking, “ Is  that monitor accurate? ” , “ What is going on ?” , “ I need to find out if this what I see is true ” , etc. We would not just pronounce the person dead and move on. Part of clarifying our thinking while performing assessments, having conversations with peers and instructors, and reading research articles is to constantly seek clarification. This takes advanced skill and is not as easy as one might think.

Here is an example.

I made a very erroneous assumption while I was a young nursing student. We had some very important assignments that were due at the end of the semester. It was noted that there were no late grace periods for those assignments as the turnaround for final grades was soon thereafter. I missed the due date. I turned it in the next day. Unfortunately, the instructor could offer no lenient point deduction for that assignment. I received a zero. My course grade dropped from an A to a B. I proceeded to get very angry at her, assuming she had the choice to let my assignment slip by since I had turned everything else in on time all semester and had received great grades on everything. I then proceeded to discuss it with another instructor and was quickly schooled that it was not the choice or decision of that particular instructor, but that it was a program policy due to the assignment being so close to the end of the semester. To this day, I regret my assumption in that the instructor was being mean. My assumption produced negative thoughts and almost resulted in me giving her a bad evaluation. Do you see how quickly it can happen? Assumptions can sometimes lead to very destructive actions that can affect others, including our patients. Assumptions are so often based on our emotions, our previous experiences in life, and others’ influences on us.

Checking Assumptions

A very important point to make is that all people make assumptions. Some assumptions are accurate, and others can really lead to mislead our thinking. The act of checking assumptions is a critical skill for critical thinkers.

Brain Workout: Let’s Practice Being Aware of and Checking Assumptions

What is an assumption you made today?

Did you assume this module was going to be complete? (It might have been blank.)

Did you assume the electricity would work?

Did you assume class would start on time? Get out early? Have a break every 50 minutes?

What is an assumption you made about the PICO statement you wrote for your EBP project?

This is usually very difficult for most people to learn the skill of checking assumptions, because they are so ingrained that people do not realize they are even making assumptions.

One way to improve your skills with checking assumptions is to consciously question your assumptions every single day. Ask me questions in class to seek clarification! I love clarifying questions and it shows me that you are ready to become a critical thinker!

Application Practice

When driving a car and you have to suddenly stop for a red light. What do you do besides brake?

Most people look in the rearview mirror to see if the car behind them is also stopping. This is checking an assumption!

Strive to be aware of checking your assumptions.

When I ride my motorcycle, I assume that I am absolutely invisible. I assume no one can see me. My superpower! My invisibility cloak. I assume that no one can see me, and this mindset helps me to be more aware of myself and cars. Sometimes, assumptions can be of help in life so that we can predict consequences.

Case Study: An Error in Judgment

A nurse stated that patients with diabetes should all be taking their medications and eating as ordered and most of them were non-compliant. She pointed to a patient with diabetes who was admitted with sepsis as an example. She said the patient had a high glucose on admission to the ICU and that is proof they were not being compliant. The patient’s physician came a few minutes later and shared that the patient was one of the most stable patients with diabetes he had ever seen in his practice. He said the patient has had normal A1C values (a lab test that measures the average blood glucose over a 3-month period) at every checkup. He said the patient’s elevated glucose was a result of the massive infection.

The nurse had judged the patient incorrectly, based on false assumptions. Had the nurse checked her assumptions, she would have noted the normal A1C value in the patient’s chart and/or withheld judgment until gathering more information from the physician. A normal A1C value in a patient who is acutely ill usually indicates the patient had been stable with diabetes until becoming acutely ill. The elevated glucose is a sign of the body’s physiological response to stress.

Now You Try! Case Study: The Patient and Pulse

A nurse was assessing a patient with a history of congestive heart failure who was just admitted to the intensive care unit with a heart rate of 30-32 and complete heart block. The physician visited with the nurse about possible causes of the complete heart block and slow heart rate. The patient stated he was faint feeling, and his blood pressure was 102/50. The patient had his medications adjusted about a month ago. The nurse was present in the patient’s room and heard the physician ask the patient if he checks his pulse at home. The patient replied, “Yes, and it is always 60.”

What are two assumptions about this case so far? List two assumptions.

The nurse was curious about the heart rate. Something did not seem right. The nurse wanted to check into how the patient checks his pulse.

What assumption is the nurse checking? (Hint: assumptions are usually the most obvious–but so obvious that they can be missed.)

The nurse asked the patient to show how he checked his pulse and asked him if he could see the clock on the wall with the second hand. He answered yes and told her which number on the clock the second hand was pointing. The nurse was checking his vision–the first assumption she was checking.

Next, the nurse asked the patient to show how he checks his pulse. The nurse felt the patient’s radial pulse while he also checked his radial pulse on his other arm. The nurse watched silently as the patient watched the clock and counted to 60. Then he stopped and said his pulse was 60. However, the nurse counted 30 beats per minute. Then she realized what happened! He watched the clock and counted to 60–he was not counting his pulse!

The nurse was checking the assumption the patient knew how to correctly count his pulse. He did not. Once the patient’s heart rate was improved, he was taught how to correctly count his pulse.

Take time to think about assumptions and EBP projects.

For example, should one assume all the staff nurses will be delighted to implement a EBP project?

Should one assume all nurses understand EBP?

Should one assume all nurses value EBP?

Will the organization support an EBP project?

Assumptions and Evidence-Based Practice

Think about the evidence-based practice topic you have chosen for your EBP project. What are two or three assumptions related to your project? Your project may be hypothetical (we won’t actually be implementing your project in a clinical setting) to learn the steps of EBP in a course. Even for a hypothetical EBP interventional project, think of some assumptions that should be checked. List your assumptions. Remember these are usually so obvious that it is easy to miss them, because they may be taken for granted.

Ideas to help start thinking:

Will supplies be needed for the project? Who will pay for the supplies? Who will order the supplies? Are the supplies expensive?

What permissions will be (if any) required for the EBP project?

Who will be involved with the EBP project?

Will staff want to participate with the EBP project?

Will staff need orientation to the EBP project?

EBP Recommendations for Interventions

Interventions based on research evidence that are suggested as part of an EBP project is one step in the process. Remember from a previous module that EBP interventions are based on research evidence, clinician expertise, and patient/family/community interventions (Schmidt & Brown, 2019). EBP recommendations are founded by current research evidence with findings that support improved outcomes for the patient/family/community. Sometimes EBP recommendations include one single intervention, while other times they are a bundle of interventions. This is where the term bundles came about in EBP. A bundle has a group of interventions implemented together because the best outcomes are found when the interventions are done together.

For the EBP project, you will write statements in the Discussion section explaining the intervention(s) based on the research evidence. Be sure to cite the research evidence on the poster to actually support the intervention choices. State exactly what you are recommending. State in clear and specific terms what is recommended. For example, if you say you recommend an adjustment of how often the central line dressings are changed, will everyone know what you mean?  However, if you say you recommend central line dressing changes be required every 48 hours, this is more specific.  Will in-service/orientation for staff be required? And if so, what will be the time needed to receive the in-service/orientation education about the interventions? The specifics will vary greatly depending on the organization and actual topic/interventions. Insight about these items should be included with the recommendations.

The Words “Proof” and “Proves” and Nursing Science

Again, back to this concept. It cannot be stressed nearly enough. Research evidence only supports what we believe to be true. The word “proof” or “proves” is not used with research as we really do not prove anything (Boswell & Cannon, 2020; Houser, 2018; Siegel, 2017).  Proof is a very strong word that means absolute or definitive. Most nursing science is relative to the times and new innovations. So, research evidence supports what is believed to be true. Avoid using the words proof and proves in nursing science.

For example, years ago, we believed the best way to provide care for patients with acute myocardial infarction was to admit them to a critical care bed with cardiac monitoring and administer morphine sulfate intravenous and xylocaine intravenous drips. Patients would be watched over as they had their myocardial infarctions. We would treat any complications as they happened.  Most patients were quite confused and delirious after the morphine/xylocaine intravenous cocktails. Many patients would describe vivid hallucinations while having their heart attacks!  One lady thought we were at the airport and wanted help with her luggage so she would not miss her flight! She was quite adamant about this hallucination and only after being weaned from her xylocaine intravenous drip, did she stop obsessing about catching the flight.  At the time, this was the best evidence available to help patients. Clinicians literally watched patients have myocardial infarctions and treated the complications as they happen. The goal was to keep them alive.

Today, interventional cardiology is used to treat patients having acute myocardial infarctions with the intent to prevent as much permanent damage as possible.  Patients are taken to the catheter lab for immediate intervention.  This dramatic change in cardiology practice is all due to the application of research evidence.  The point is this:  what we believe to be true is relevant to the time and research evidence available. This is why we avoid using prove or proof in nursing and health sciences. We do not seek to prove; we seek to advance the research evidence and application of research evidence in practice.  We use evidence to support practices that promote the best outcomes for patients/families/communities.

Dissemination is extremely important. It simply means “getting the findings of research to the people who can make use of them”. This step is often either delayed or never occurs. Dissemination usually occurs either by written or spoken word. The traditional means to dissemination include academic publishing (e.g. academic journals) and conferences and workshops (e.g. posters, presentations, etc.). It “seems” easy, right? However, unfortunately, there are many reasons that findings are never shared. Mainly, it takes a lot of effort. It is laborious to get published. It often requires financial backing to attend a conference.

To disseminate our EBP Projects, we will be conducting a semi-formal poster session-style presentation much like at a conference setting. It is recommended that you should introduce your poster presentation with a “1 Minute Pitch” that can sometimes stretch a bit longer than one minute. You don’t want to “give everything away” so to speak, but rather capture the audience’s interest, introduce yourself and the project, and spark a dialogue. We will spend time in class going over the parameters for presentation.

References & Attribution

“ Green check mark ” by rawpixel licensed CC0 .

“ Light bulb doodle ” by rawpixel licensed CC0 .

“ Orange flame ” by rawpixel licensed CC0 .

Boswell, C. & Cannon, S. (2020). Introduction to nursing research: Incorporating evidence-based practice (5th ed.). Jones & Bartlett Learning.

Brookfield, S. (1987). Challenging adults to explore alternative ways of thinking and acting. Jossey-Bass, Inc., Publishers. 

Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th ed.). Jones & Bartlett Learning.

Paul, R. & Elder, L. (2008).  Critical thinking: The art of Socratic questioning, part III.   Journal of Developmental Education, 31 (3), 34-35.   Retrieved from https://eric.ed.gov/?id=EJ832681

Schmidt, N. A. & Brown, J. M. (2019). Evidence-based practice for nurses: Appraisal and application of research (4th ed.). Jones & Bartlett Learning.

Seigel, E. (2017). Scientific proof is a myth. Forbes , (11), Retrieved from https://www.forbes.com/sites/startswithabang/2017/11/22/scientific-proof-is-a-myth/#3f6972672fb1

Evidence-Based Practice & Research Methodologies Copyright © by Tracy Fawns is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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25 Assumptions Examples

Assumptions are fundamental beliefs that we accept as true without proof or empirical evidence for their claims.

Often, our assumptions are subconscious. We don’t realize that many of our claims and beliefs have a range of underpinning assumptions that have not been sufficiently scrutinized.

So, critical thinking is necessary to analyze and challenge our own assumptions as well as those presented by others. By turning the spotlight on the assumptions underpinning belief systems, we can adjust, refine, improve, or even outright reject assumptions that are established on faulty logic.

Assumptions Examples

1. cultural ignorance.

Example: “Everyone Celebrates Christmas”

Cultural Ignorance is an assumption that mistakenly universalizes one’s own cultural norms.

For instance, the belief “Everyone Celebrates Christmas” simplifies the rich tapestry of global cultural practices down to the singular tradition familiar to the person holding this assumption. This kind of assumption can lead to misunderstanding and miscommunication, and it highlights the importance of cultural awareness and sensitivity.

2. False Consensus Bias

Example: “Other People Think Like Me”

False Consensus Bias refers to a cognitive bias that causes people to overestimate the extent to which their beliefs, values, characteristics, and behaviors are shared by others.

In the instance of the assumption “Other People Think Like Me”, individuals believe that their personal viewpoints are the norm. This error in judgment can lead to a lack of empathy and understanding of others’ experiences.

See More: False Consensus Effect Examples

3. Fundamental Attribution Error

Example: “That Person’s just Incompetent”

The Fundamental Attribution Error is a cognitive bias where we overemphasize personal characteristics and ignore situational influences when judging others’ behavior.

For example, concluding “That Person’s Incompetent” after observing a single mistake overlooks the potential role of situational factors, such as stress or lack of resources. It’s common when judging car accidents, where we assume someone’s a bad driver and don’t pay attention to more complex factors that contributed to the accent. It’s important to avoid this bias to make balanced, fair judgments about others.

See More: Fundamental Attribution Error Examples

Case Study: Occam’s Razor as a Framework for making Assumptions

Occam’s Razor helps us to make assumptions with minimum possible variables. This concept argues that the more possible variables in the assumption, the more chances there are for us to make mistakes. From this perspective, we could claim that the simplest answer is most likely the correct answer as the simplest answer contains the minimum possible assumptions. However, this view could be reframed with the following counterargument : the more inputs we have, the more chances we have of making an informed decision.

So, what do you think? Is Occam’s Razor a good framework for making assumptions?

4. Gender Bias

Example: “The Man must be the Doctor”

Gender Bias is an unfounded inclination or prejudice for or against one gender in comparison to the other. This is an often implicit assumption we’ve received from internalizing cultural stereotypes throughout our lifetimes.

The assumption “The Man must be the Doctor” exemplifies gender bias, whereby certain occupations are stereotype-anchored to specific genders. Gender bias can foster discrimination and inequity and impede social progress.

See More: Gender Bias Examples

5. Halo Effect

Example: “She’s Good at This, so she Must be Good at That”

The Halo Effect is a cognitive bias that influences how we perceive other’s abilities based on our overall impression of them.

The statement “She’s Good at This, so she Must be Good at That” is a typical manifestation of the Halo Effect. Here, a person’s proficiency in one area is mistakenly projected onto their capabilities in unrelated areas. In other words, we assume someone is good at everything because they’re good at one thing.

See More: Halo Effect Examples

6. Hindsight Bias

Example: “How did they not Foresee That Outcome?”

Hindsight Bias, also known as the “knew-it-all-along” phenomenon, is the tendency for people to assume that events that have already occurred would have been more predictable than they were before they took place.

An example is the question “How did they not Foresee That Outcome?” which overlooks the fact that predicting an outcome with certainty was not possible before it happened. Hindsight bias leads to oversimplification of decision-making processes and overlooks the complexity of situations.

See More: Hindsight Bias Examples

7. Just-World Bias

Example: “He Probably Deserved his Misfortune”

Just-World Bias occurs when we tend to assume that justice will prevail in the universe. As a result, we tend to falsely attribute consequences to moral reasons, maintaining the belief that the universe is fundamentally just.

In the case of the assumption “He Probably Deserved his Misfortune”, we’re assuming that the person deserved whatever misfortune they stumbled upon. This assumption, however, can lead to blame-victim mentality and hinder the development of empathy.

8. Optimism Bias

Example: “It will all Work Out”

Optimism Bias refers to the assumption that positive outcomes will happen in the future, often to a greater extent than is objectively likely.

The statement “It will all Work Out” is an example of this bias, where a person irrationally anticipates the best possible outcome. While optimism can be beneficial, this generalized assumption might lead to poor decision-making if the potential for negative outcomes is not considered.

9. Overgeneralization Bias

Example: “Everything must be Like This”

Overgeneralization Bias occurs when individuals extend a general rule to assume it fits into a broad set of scenarios.

The idea “Everything must be Like This” reflects this bias, portraying a mental shortcut where specific experiences or examples dictate our view on the entirety of a category. Such assumptions can lead to misinterpretations and misunderstandings, thus it’s essential to avoid this bias.

10. Stereotyping

Example: “All teenagers are rebellious.”

Stereotyping is making assumptions about a group of people based on incomplete or distorted information.

With the assumption “All teenagers are rebellious,” we assign characteristics to all members of the group regardless of individual differences. This can lead to prejudice and discrimination, undermining the complex and unique nature of individuals in a group.

See More: Types of Stereotypes

11. Confirmation Bias

Example: “I knew he was like that because he did that one thing.”

Confirmation Bias is our tendency to favor and emphasize information that confirms what we already believe, while ignoring conflicting data.

In the case of “I knew he was like that because he did that one thing,” confirmation bias is at play. We overlook contrary evidence and amplify one piece of confirming evidence. This assumption can prevent us from forming accurate views based on comprehensive data.

See More: Confirmation Bias Examples

12. Availability Heuristic

Example: “I’ve seen it happen a lot recently, so it must be common.”

Availability Heuristic is a mental shortcut which inclines us to make judgments based on immediate and salient examples in our minds, rather than examining the larger context or statistical reality.

In the assumption “I’ve seen it happen a lot recently, so it must be common,” we make a broad assumption based on a few recent examples. Therefore, we might overlook the larger picture and form incorrect beliefs.

See More: Availability Heuristic Examples

13. Projection

Example: “I don’t trust him because he probably thinks the same way I do.”

Projection is a psychological defense mechanism where individuals attribute their own unacceptable thoughts, feelings, or motives to another person.

The statement “I don’t trust him because he probably thinks the same way I do” is an example of projection. Here, the lack of trust isn’t based on objective judgment, but stems from personal insecurities projected onto another person. It’s important to recognize that this assumption says more about the person making it than about the person it’s directed towards.

14. Anchoring Bias

Example: “The first piece of information I received about them must be the most accurate.”

Anchoring Bias is a cognitive bias where individuals rely too heavily on an initial piece of information (the “anchor”) when making decisions.

Under the influence of the “The first piece of information I received about them must be the most accurate” assumption, one neglects the potential for complexity, change, or additional information. This can lead to an oversimplified understanding of people and situations.

See More: Anchoring Bias Examples

15. Fixed Mindset

Example: “I cannot improve, no matter how hard I try.”

Fixed Mindset is a belief an individual has about their abilities and talents as being unalterable, static characteristics.

In the case of the “I cannot improve, no matter how hard I try” assumption, an individual believes that their abilities are set in stone. This mindset constrains personal and professional growth by discouraging effort and resilience.

To learn more about this concept, coined by psychologist Carol Dweck, read the following guides:

• Fixed Mindset Examples
• Growth Mindset Examples

16. Self-Handicapping

Example: “I could have done it if I had tried.”

Self-Handicapping is a cognitive strategy where people create obstacles and excuses to avoid self-blame when they do poorly.

With the assumption, “I could have done it if I had tried,” the person is creating a safety net to protect their ego from potential failure. This assumption can lead to a pattern of poor performance, as it may prevent a person from pursuing challenges and trying their best.

17. Illusion of Control

Example: “I can control or influence this outcome more than I actually can.”

The Illusion of Control is a psychological mechanism where a person overestimates their ability to control events that are largely, if not entirely, made of chance occurrences.

For example, a person claiming “I can control or influence this outcome more than I actually can” falls into this illusion. While it can create confidence, this assumption can lead to disappointment when actual control doesn’t match perceived control.

18. Endowment Effect

Example: “What I own is more valuable just because it’s mine.”

The Endowment Effect is a psychological bias that causes individuals to overvalue things simply because they own them.

With the assumption, “What I own is more valuable just because it’s mine,” the person overlooks the objective value of an item in favor of its subjective, personal value. This bias can lead to unrealistic expectations and hinders the ability to see things unbiasedly.

19. Negativity Bias

Example: “I remember my failures more than my successes, so I must be a failure.”

Negativity Bias is the tendency to give more weight and attention to negative experiences or information than to equal positive ones.

In “I remember my failures more than my successes, so I must be a failure,” your focus is on negative events. This bias impacts your self-image, and it can become detrimental to your mental health if not balanced with positives.

Read More: Negativity Bias Examples

20. Illusory Superiority

Example: “I’m better than average at this task.”

Illusory Superiority is the perception that our abilities are above average, irrespective of reality. This cognitive bias is often due to overconfidence.

The assumption “I’m better than average at this task,” indicates this bias. It can lead us to downplay our weaknesses or underestimate the capabilities of others.

See More: Overconfidence Bias Examples

21. Planning Fallacy

Example: “I can get this done (faster than I actually can).”

Planning Fallacy is a cognitive bias that results in an individual underestimating the time required to complete a future task.

An underestimation is a poor assumption . For example, in the statement, “I can get this done faster than I actually can,” you overestimate your efficiency. This bias disrupts productivity and can lead to time management challenges.

22. Status Quo Bias

Example: “Things should stay the way they are because that’s how they’ve always been.”

Status Quo Bias is a psychological preference for the current state of affairs, resisting change due to comfort and familiarity with the existing situation.

The assumption “Things should stay the way they are because that’s how they’ve always been” is an example of the Status Quo Bias. This can prevent improvements, innovations, or necessary changes from being made.

See More: Status Quo Examples

23. Survivorship Bias

Example: “Successful people did X, so doing X will make me successful.”

Survivorship Bias is a logical error of focusing on the people or things that have “survived” some process and inadvertently overlooking those that didn’t because of their lack of visibility.

In the statement “Successful people did X, so doing X will make me successful,” you are neglecting the many people who may have done “X” but did not succeed. This can lead to misguided career or life choices based on incomplete information.

See More: Survivorship Bias Examples

24. Zero-Sum Bias

Example: “If someone else gains, I must lose.”

Zero-Sum Bias is the assumption that one individual’s gain is another’s loss, as if there’s a finite amount of success, wealth, or happiness in the world.

The statement “If someone else gains, I must lose” showcases a typical zero-sum mentality. It doesn’t take into account the possibilities for mutual benefits or shared success. This assumption can limit cooperation and create unnecessary competition.

25. Gambler’s Fallacy

Example: “I’ve lost three times in a row, so I’m due for a win.”

The Gambler’s Fallacy is the erroneous assumption that if a certain event occurs more frequently than normal during a given period, it will happen less frequently in the future (or vice versa).

In the example “I’ve lost three times in a row, so I’m due for a win,” the person wrongly assumes that previous losses increase the probability of future wins. This flawed assumption can lead to poor decision-making, particularly in situations involving risk.

See More: Gambler’s Fallacy Examples

Not all assumptions are wrong. In fact, oftentimes, our intuition is correct. And intuition is based on assuming things without explicit evidence.

Nevertheless, we need to constantly examine all the underlying assumptions in our thoughts and beliefs. Through this introspective process, we can improve our thought processes and lead to better results.

Furthermore, by examining the assumptions of our opponents during debates, we might be able to find fallacies and flawed heuristics that can help us rebut their points and come up with a strong refutation .

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 5 Top Tips for Succeeding at University
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 50 Durable Goods Examples
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 100 Consumer Goods Examples
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 30 Globalization Pros and Cons

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Get science-backed answers as you write with Paperpal's Research feature

How to Write a Hypothesis? Types and Examples 

All research studies involve the use of the scientific method, which is a mathematical and experimental technique used to conduct experiments by developing and testing a hypothesis or a prediction about an outcome. Simply put, a hypothesis is a suggested solution to a problem. It includes elements that are expressed in terms of relationships with each other to explain a condition or an assumption that hasn’t been verified using facts. 1 The typical steps in a scientific method include developing such a hypothesis, testing it through various methods, and then modifying it based on the outcomes of the experiments.  

A research hypothesis can be defined as a specific, testable prediction about the anticipated results of a study. 2 Hypotheses help guide the research process and supplement the aim of the study. After several rounds of testing, hypotheses can help develop scientific theories. 3 Hypotheses are often written as if-then statements. 

Here are two hypothesis examples: 

Dandelions growing in nitrogen-rich soils for two weeks develop larger leaves than those in nitrogen-poor soils because nitrogen stimulates vegetative growth. 4  

If a company offers flexible work hours, then their employees will be happier at work. 5  

Table of Contents

• What is a hypothesis? 
• Types of hypotheses 
• Characteristics of a hypothesis 
• Functions of a hypothesis 
• How to write a hypothesis 
• Hypothesis examples 
• Frequently asked questions 

What is a hypothesis?

A hypothesis expresses an expected relationship between variables in a study and is developed before conducting any research. Hypotheses are not opinions but rather are expected relationships based on facts and observations. They help support scientific research and expand existing knowledge. An incorrectly formulated hypothesis can affect the entire experiment leading to errors in the results so it’s important to know how to formulate a hypothesis and develop it carefully.

A few sources of a hypothesis include observations from prior studies, current research and experiences, competitors, scientific theories, and general conditions that can influence people. Figure 1 depicts the different steps in a research design and shows where exactly in the process a hypothesis is developed. 4  

There are seven different types of hypotheses—simple, complex, directional, nondirectional, associative and causal, null, and alternative. 

Types of hypotheses

The seven types of hypotheses are listed below: 5 , 6,7  

• Simple : Predicts the relationship between a single dependent variable and a single independent variable. 

Example: Exercising in the morning every day will increase your productivity.  

• Complex : Predicts the relationship between two or more variables. 

Example: Spending three hours or more on social media daily will negatively affect children’s mental health and productivity, more than that of adults.  

• Directional : Specifies the expected direction to be followed and uses terms like increase, decrease, positive, negative, more, or less. 

Example: The inclusion of intervention X decreases infant mortality compared to the original treatment.  

• Non-directional : Does not predict the exact direction, nature, or magnitude of the relationship between two variables but rather states the existence of a relationship. This hypothesis may be used when there is no underlying theory or if findings contradict prior research. 

Example: Cats and dogs differ in the amount of affection they express.  

• Associative and causal : An associative hypothesis suggests an interdependency between variables, that is, how a change in one variable changes the other.  

Example: There is a positive association between physical activity levels and overall health.  

A causal hypothesis, on the other hand, expresses a cause-and-effect association between variables. 

Example: Long-term alcohol use causes liver damage.  

• Null : Claims that the original hypothesis is false by showing that there is no relationship between the variables. 

Example: Sleep duration does not have any effect on productivity.  

• Alternative : States the opposite of the null hypothesis, that is, a relationship exists between two variables. 

Example: Sleep duration affects productivity.  

Characteristics of a hypothesis

So, what makes a good hypothesis? Here are some important characteristics of a hypothesis. 8,9  

• Testable : You must be able to test the hypothesis using scientific methods to either accept or reject the prediction. 
• Falsifiable : It should be possible to collect data that reject rather than support the hypothesis. 
• Logical : Hypotheses shouldn’t be a random guess but rather should be based on previous theories, observations, prior research, and logical reasoning. 
• Positive : The hypothesis statement about the existence of an association should be positive, that is, it should not suggest that an association does not exist. Therefore, the language used and knowing how to phrase a hypothesis is very important. 
• Clear and accurate : The language used should be easily comprehensible and use correct terminology. 
• Relevant : The hypothesis should be relevant and specific to the research question. 
• Structure : Should include all the elements that make a good hypothesis: variables, relationship, and outcome. 

Functions of a hypothesis

The following list mentions some important functions of a hypothesis: 1  

• Maintains the direction and progress of the research. 
• Expresses the important assumptions underlying the proposition in a single statement. 
• Establishes a suitable context for researchers to begin their investigation and for readers who are referring to the final report. 
• Provides an explanation for the occurrence of a specific phenomenon. 
• Ensures selection of appropriate and accurate facts necessary and relevant to the research subject. 

To summarize, a hypothesis provides the conceptual elements that complete the known data, conceptual relationships that systematize unordered elements, and conceptual meanings and interpretations that explain the unknown phenomena. 1  

How to write a hypothesis

Listed below are the main steps explaining how to write a hypothesis. 2,4,5  

• Make an observation and identify variables : Observe the subject in question and try to recognize a pattern or a relationship between the variables involved. This step provides essential background information to begin your research.  

For example, if you notice that an office’s vending machine frequently runs out of a specific snack, you may predict that more people in the office choose that snack over another. 

• Identify the main research question : After identifying a subject and recognizing a pattern, the next step is to ask a question that your hypothesis will answer.  

For example, after observing employees’ break times at work, you could ask “why do more employees take breaks in the morning rather than in the afternoon?” 

• Conduct some preliminary research to ensure originality and novelty : Your initial answer, which is your hypothesis, to the question is based on some pre-existing information about the subject. However, to ensure that your hypothesis has not been asked before or that it has been asked but rejected by other researchers you would need to gather additional information.  

For example, based on your observations you might state a hypothesis that employees work more efficiently when the air conditioning in the office is set at a lower temperature. However, during your preliminary research you find that this hypothesis was proven incorrect by a prior study. 

• Develop a general statement : After your preliminary research has confirmed the originality of your proposed answer, draft a general statement that includes all variables, subjects, and predicted outcome. The statement could be if/then or declarative.  
• Finalize the hypothesis statement : Use the PICOT model, which clarifies how to word a hypothesis effectively, when finalizing the statement. This model lists the important components required to write a hypothesis. 

P opulation: The specific group or individual who is the main subject of the research 

I nterest: The main concern of the study/research question 

C omparison: The main alternative group 

O utcome: The expected results  

T ime: Duration of the experiment 

Once you’ve finalized your hypothesis statement you would need to conduct experiments to test whether the hypothesis is true or false. 

Hypothesis examples

The following table provides examples of different types of hypotheses. 10 ,11  

Key takeaways  

Here’s a summary of all the key points discussed in this article about how to write a hypothesis. 

• A hypothesis is an assumption about an association between variables made based on limited evidence, which should be tested. 
• A hypothesis has four parts—the research question, independent variable, dependent variable, and the proposed relationship between the variables.   
• The statement should be clear, concise, testable, logical, and falsifiable. 
• There are seven types of hypotheses—simple, complex, directional, non-directional, associative and causal, null, and alternative. 
• A hypothesis provides a focus and direction for the research to progress. 
• A hypothesis plays an important role in the scientific method by helping to create an appropriate experimental design. 

Frequently asked questions

Hypotheses and research questions have different objectives and structure. The following table lists some major differences between the two. 9  

Here are a few examples to differentiate between a research question and hypothesis. 

Yes, here’s a simple checklist to help you gauge the effectiveness of your hypothesis. 9   1. When writing a hypothesis statement, check if it:  2. Predicts the relationship between the stated variables and the expected outcome.  3. Uses simple and concise language and is not wordy.  4. Does not assume readers’ knowledge about the subject.  5. Has observable, falsifiable, and testable results. 

As mentioned earlier in this article, a hypothesis is an assumption or prediction about an association between variables based on observations and simple evidence. These statements are usually generic. Research objectives, on the other hand, are more specific and dictated by hypotheses. The same hypothesis can be tested using different methods and the research objectives could be different in each case.     For example, Louis Pasteur observed that food lasts longer at higher altitudes, reasoned that it could be because the air at higher altitudes is cleaner (with fewer or no germs), and tested the hypothesis by exposing food to air cleaned in the laboratory. 12 Thus, a hypothesis is predictive—if the reasoning is correct, X will lead to Y—and research objectives are developed to test these predictions. 

Null hypothesis testing is a method to decide between two assumptions or predictions between variables (null and alternative hypotheses) in a statistical relationship in a sample. The null hypothesis, denoted as H 0 , claims that no relationship exists between variables in a population and any relationship in the sample reflects a sampling error or occurrence by chance. The alternative hypothesis, denoted as H 1 , claims that there is a relationship in the population. In every study, researchers need to decide whether the relationship in a sample occurred by chance or reflects a relationship in the population. This is done by hypothesis testing using the following steps: 13   1. Assume that the null hypothesis is true.  2. Determine how likely the sample relationship would be if the null hypothesis were true. This probability is called the p value.  3. If the sample relationship would be extremely unlikely, reject the null hypothesis and accept the alternative hypothesis. If the relationship would not be unlikely, accept the null hypothesis. 

To summarize, researchers should know how to write a good hypothesis to ensure that their research progresses in the required direction. A hypothesis is a testable prediction about any behavior or relationship between variables, usually based on facts and observation, and states an expected outcome.  

We hope this article has provided you with essential insight into the different types of hypotheses and their functions so that you can use them appropriately in your next research project. 

References  

• Dalen, DVV. The function of hypotheses in research. Proquest website. Accessed April 8, 2024. https://www.proquest.com/docview/1437933010?pq-origsite=gscholar&fromopenview=true&sourcetype=Scholarly%20Journals&imgSeq=1  
• McLeod S. Research hypothesis in psychology: Types & examples. SimplyPsychology website. Updated December 13, 2023. Accessed April 9, 2024. https://www.simplypsychology.org/what-is-a-hypotheses.html  
• Scientific method. Britannica website. Updated March 14, 2024. Accessed April 9, 2024. https://www.britannica.com/science/scientific-method  
• The hypothesis in science writing. Accessed April 10, 2024. https://berks.psu.edu/sites/berks/files/campus/HypothesisHandout_Final.pdf  
• How to develop a hypothesis (with elements, types, and examples). Indeed.com website. Updated February 3, 2023. Accessed April 10, 2024. https://www.indeed.com/career-advice/career-development/how-to-write-a-hypothesis  
• Types of research hypotheses. Excelsior online writing lab. Accessed April 11, 2024. https://owl.excelsior.edu/research/research-hypotheses/types-of-research-hypotheses/  
• What is a research hypothesis: how to write it, types, and examples. Researcher.life website. Published February 8, 2023. Accessed April 11, 2024. https://researcher.life/blog/article/how-to-write-a-research-hypothesis-definition-types-examples/  
• Developing a hypothesis. Pressbooks website. Accessed April 12, 2024. https://opentext.wsu.edu/carriecuttler/chapter/developing-a-hypothesis/  
• What is and how to write a good hypothesis in research. Elsevier author services website. Accessed April 12, 2024. https://scientific-publishing.webshop.elsevier.com/manuscript-preparation/what-how-write-good-hypothesis-research/  
• How to write a great hypothesis. Verywellmind website. Updated March 12, 2023. Accessed April 13, 2024. https://www.verywellmind.com/what-is-a-hypothesis-2795239  
• 15 Hypothesis examples. Helpfulprofessor.com Published September 8, 2023. Accessed March 14, 2024. https://helpfulprofessor.com/hypothesis-examples/ 
• Editage insights. What is the interconnectivity between research objectives and hypothesis? Published February 24, 2021. Accessed April 13, 2024. https://www.editage.com/insights/what-is-the-interconnectivity-between-research-objectives-and-hypothesis  
• Understanding null hypothesis testing. BCCampus open publishing. Accessed April 16, 2024. https://opentextbc.ca/researchmethods/chapter/understanding-null-hypothesis-testing/#:~:text=In%20null%20hypothesis%20testing%2C%20this,said%20to%20be%20statistically%20significant  

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Phenomenological Assumptions and Knowledge Dissemination within Organizational Studies

• Explicating assumptions underlying academic research may make new information more transparent and easily adopted.
• Assumptions can pose a barrier limiting the integration of knowledge generated within a subfield into the broader intellectual discourse of its field.
• Specifically, assumptions that negotiations are one-shot "at the table" interactions make it more difficult for non-negotiations organizational scholars to recognize and appreciate the relevance of the findings to broader organizational research.
• The negotiation studies in this data set, spanning 15 years of published research in top-tier journals, seldom were explicit about the assumptions made and seldom acknowledged reasonable boundary conditions for their findings.

Author Abstract

Phenomenological assumptions—assumptions about the fundamental qualities of the phenomenon being studied and how it relates to the environment in which it occurs—affect the dissemination of knowledge from sub-fields to the broader field of study. Micro-process research in organizational studies rests on implicit phenomenological assumptions that vary in the extent to which micro-processes are viewed as parts of larger systems. We suggest that phenomenological assumptions linking micro-processes to organizational contexts highlight the relevance of micro-process research findings to broader organizational questions, and therefore increase the likelihood that the findings will disseminate to the larger field of organizational research. We test this assertion by analyzing studies of negotiation published in top peer-reviewed management, psychology, sociology, and industrial relations journals from 1990 to 2005. Our findings illuminate a continuum of open systems to closed systems phenomenological assumptions revealed in this micro-process research. Analysis of the citation rates of the articles in our data set by non-negotiation organizational research indicates that more open systems assumptions increase the likelihood that a negotiation article will be cited in organizational studies, after controlling for other, previously identified effects on citation rates. Our findings suggest that sub-fields can increase the impact they have on the broader intellectual discourse by situating their phenomena in rich contexts that illuminate the connections between their findings and questions of interest to the broader field. 48 pages.

Paper Information

• Full Working Paper Text
• Working Paper Publication Date: September 2008, revised March 2009
• HBS Working Paper Number: 09-043
• Faculty Unit(s): Negotiation, Organizations & Markets
• 01 May 2024
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Home » Research Methodology – Types, Examples and writing Guide

Research Methodology – Types, Examples and writing Guide

Table of Contents

Research Methodology

Definition:

Research Methodology refers to the systematic and scientific approach used to conduct research, investigate problems, and gather data and information for a specific purpose. It involves the techniques and procedures used to identify, collect , analyze , and interpret data to answer research questions or solve research problems . Moreover, They are philosophical and theoretical frameworks that guide the research process.

Structure of Research Methodology

Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section:

I. Introduction

• Provide an overview of the research problem and the need for a research methodology section
• Outline the main research questions and objectives

II. Research Design

• Explain the research design chosen and why it is appropriate for the research question(s) and objectives
• Discuss any alternative research designs considered and why they were not chosen
• Describe the research setting and participants (if applicable)

III. Data Collection Methods

• Describe the methods used to collect data (e.g., surveys, interviews, observations)
• Explain how the data collection methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or instruments used for data collection

IV. Data Analysis Methods

• Describe the methods used to analyze the data (e.g., statistical analysis, content analysis )
• Explain how the data analysis methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or software used for data analysis

V. Ethical Considerations

• Discuss any ethical issues that may arise from the research and how they were addressed
• Explain how informed consent was obtained (if applicable)
• Detail any measures taken to ensure confidentiality and anonymity

VI. Limitations

• Identify any potential limitations of the research methodology and how they may impact the results and conclusions

VII. Conclusion

• Summarize the key aspects of the research methodology section
• Explain how the research methodology addresses the research question(s) and objectives

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

This is a research methodology that involves the collection and analysis of numerical data using statistical methods. This type of research is often used to study cause-and-effect relationships and to make predictions.

Qualitative Research Methodology

This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.

Mixed-Methods Research Methodology

This is a research methodology that combines elements of both quantitative and qualitative research. This approach can be particularly useful for studies that aim to explore complex phenomena and to provide a more comprehensive understanding of a particular topic.

Case Study Research Methodology

This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group.

Action Research Methodology

This is a research methodology that involves a collaborative process between researchers and practitioners to identify and solve real-world problems. Action research is often used in education, healthcare, and social work.

Experimental Research Methodology

This is a research methodology that involves the manipulation of one or more independent variables to observe their effects on a dependent variable. Experimental research is often used to study cause-and-effect relationships and to make predictions.

Survey Research Methodology

This is a research methodology that involves the collection of data from a sample of individuals using questionnaires or interviews. Survey research is often used to study attitudes, opinions, and behaviors.

Grounded Theory Research Methodology

This is a research methodology that involves the development of theories based on the data collected during the research process. Grounded theory is often used in sociology and anthropology to generate theories about social phenomena.

Research Methodology Example

An Example of Research Methodology could be the following:

Research Methodology for Investigating the Effectiveness of Cognitive Behavioral Therapy in Reducing Symptoms of Depression in Adults

Introduction:

The aim of this research is to investigate the effectiveness of cognitive-behavioral therapy (CBT) in reducing symptoms of depression in adults. To achieve this objective, a randomized controlled trial (RCT) will be conducted using a mixed-methods approach.

Research Design:

The study will follow a pre-test and post-test design with two groups: an experimental group receiving CBT and a control group receiving no intervention. The study will also include a qualitative component, in which semi-structured interviews will be conducted with a subset of participants to explore their experiences of receiving CBT.

Participants:

Participants will be recruited from community mental health clinics in the local area. The sample will consist of 100 adults aged 18-65 years old who meet the diagnostic criteria for major depressive disorder. Participants will be randomly assigned to either the experimental group or the control group.

Intervention :

The experimental group will receive 12 weekly sessions of CBT, each lasting 60 minutes. The intervention will be delivered by licensed mental health professionals who have been trained in CBT. The control group will receive no intervention during the study period.

Data Collection:

Quantitative data will be collected through the use of standardized measures such as the Beck Depression Inventory-II (BDI-II) and the Generalized Anxiety Disorder-7 (GAD-7). Data will be collected at baseline, immediately after the intervention, and at a 3-month follow-up. Qualitative data will be collected through semi-structured interviews with a subset of participants from the experimental group. The interviews will be conducted at the end of the intervention period, and will explore participants’ experiences of receiving CBT.

Data Analysis:

Quantitative data will be analyzed using descriptive statistics, t-tests, and mixed-model analyses of variance (ANOVA) to assess the effectiveness of the intervention. Qualitative data will be analyzed using thematic analysis to identify common themes and patterns in participants’ experiences of receiving CBT.

Ethical Considerations:

This study will comply with ethical guidelines for research involving human subjects. Participants will provide informed consent before participating in the study, and their privacy and confidentiality will be protected throughout the study. Any adverse events or reactions will be reported and managed appropriately.

Data Management:

All data collected will be kept confidential and stored securely using password-protected databases. Identifying information will be removed from qualitative data transcripts to ensure participants’ anonymity.

Limitations:

One potential limitation of this study is that it only focuses on one type of psychotherapy, CBT, and may not generalize to other types of therapy or interventions. Another limitation is that the study will only include participants from community mental health clinics, which may not be representative of the general population.

Conclusion:

This research aims to investigate the effectiveness of CBT in reducing symptoms of depression in adults. By using a randomized controlled trial and a mixed-methods approach, the study will provide valuable insights into the mechanisms underlying the relationship between CBT and depression. The results of this study will have important implications for the development of effective treatments for depression in clinical settings.

How to Write Research Methodology

Writing a research methodology involves explaining the methods and techniques you used to conduct research, collect data, and analyze results. It’s an essential section of any research paper or thesis, as it helps readers understand the validity and reliability of your findings. Here are the steps to write a research methodology:

• Start by explaining your research question: Begin the methodology section by restating your research question and explaining why it’s important. This helps readers understand the purpose of your research and the rationale behind your methods.
• Describe your research design: Explain the overall approach you used to conduct research. This could be a qualitative or quantitative research design, experimental or non-experimental, case study or survey, etc. Discuss the advantages and limitations of the chosen design.
• Discuss your sample: Describe the participants or subjects you included in your study. Include details such as their demographics, sampling method, sample size, and any exclusion criteria used.
• Describe your data collection methods : Explain how you collected data from your participants. This could include surveys, interviews, observations, questionnaires, or experiments. Include details on how you obtained informed consent, how you administered the tools, and how you minimized the risk of bias.
• Explain your data analysis techniques: Describe the methods you used to analyze the data you collected. This could include statistical analysis, content analysis, thematic analysis, or discourse analysis. Explain how you dealt with missing data, outliers, and any other issues that arose during the analysis.
• Discuss the validity and reliability of your research : Explain how you ensured the validity and reliability of your study. This could include measures such as triangulation, member checking, peer review, or inter-coder reliability.
• Acknowledge any limitations of your research: Discuss any limitations of your study, including any potential threats to validity or generalizability. This helps readers understand the scope of your findings and how they might apply to other contexts.
• Provide a summary: End the methodology section by summarizing the methods and techniques you used to conduct your research. This provides a clear overview of your research methodology and helps readers understand the process you followed to arrive at your findings.

When to Write Research Methodology

Research methodology is typically written after the research proposal has been approved and before the actual research is conducted. It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project.

The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.

The methodology should be written in a clear and concise manner, and it should be based on established research practices and standards. It is important to provide enough detail so that the reader can understand how the research was conducted and evaluate the validity of the results.

Applications of Research Methodology

Here are some of the applications of research methodology:

• To identify the research problem: Research methodology is used to identify the research problem, which is the first step in conducting any research.
• To design the research: Research methodology helps in designing the research by selecting the appropriate research method, research design, and sampling technique.
• To collect data: Research methodology provides a systematic approach to collect data from primary and secondary sources.
• To analyze data: Research methodology helps in analyzing the collected data using various statistical and non-statistical techniques.
• To test hypotheses: Research methodology provides a framework for testing hypotheses and drawing conclusions based on the analysis of data.
• To generalize findings: Research methodology helps in generalizing the findings of the research to the target population.
• To develop theories : Research methodology is used to develop new theories and modify existing theories based on the findings of the research.
• To evaluate programs and policies : Research methodology is used to evaluate the effectiveness of programs and policies by collecting data and analyzing it.
• To improve decision-making: Research methodology helps in making informed decisions by providing reliable and valid data.

Purpose of Research Methodology

Research methodology serves several important purposes, including:

• To guide the research process: Research methodology provides a systematic framework for conducting research. It helps researchers to plan their research, define their research questions, and select appropriate methods and techniques for collecting and analyzing data.
• To ensure research quality: Research methodology helps researchers to ensure that their research is rigorous, reliable, and valid. It provides guidelines for minimizing bias and error in data collection and analysis, and for ensuring that research findings are accurate and trustworthy.
• To replicate research: Research methodology provides a clear and detailed account of the research process, making it possible for other researchers to replicate the study and verify its findings.
• To advance knowledge: Research methodology enables researchers to generate new knowledge and to contribute to the body of knowledge in their field. It provides a means for testing hypotheses, exploring new ideas, and discovering new insights.
• To inform decision-making: Research methodology provides evidence-based information that can inform policy and decision-making in a variety of fields, including medicine, public health, education, and business.

Advantages of Research Methodology

Research methodology has several advantages that make it a valuable tool for conducting research in various fields. Here are some of the key advantages of research methodology:

• Systematic and structured approach : Research methodology provides a systematic and structured approach to conducting research, which ensures that the research is conducted in a rigorous and comprehensive manner.
• Objectivity : Research methodology aims to ensure objectivity in the research process, which means that the research findings are based on evidence and not influenced by personal bias or subjective opinions.
• Replicability : Research methodology ensures that research can be replicated by other researchers, which is essential for validating research findings and ensuring their accuracy.
• Reliability : Research methodology aims to ensure that the research findings are reliable, which means that they are consistent and can be depended upon.
• Validity : Research methodology ensures that the research findings are valid, which means that they accurately reflect the research question or hypothesis being tested.
• Efficiency : Research methodology provides a structured and efficient way of conducting research, which helps to save time and resources.
• Flexibility : Research methodology allows researchers to choose the most appropriate research methods and techniques based on the research question, data availability, and other relevant factors.
• Scope for innovation: Research methodology provides scope for innovation and creativity in designing research studies and developing new research techniques.

Research Methodology Vs Research Methods

About the author.

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Project Bliss

How to create a project assumptions list: examples and template included.

When my daughter was very little, she came home from school one day and told me the saying about assumptions: When you assume, you make an ass out of you and me.

Gasp! “Where did you hear that, honey?”

“At school, Mommy. Our teacher told us.”

The class was shocked and amazed because their teacher had used the word “ass.”

This was back when they still thought “butt” was a bad word.

We’ve all heard that one.

I just didn’t expect my little one to learn that saying so early in her life.

Though it’s often true, that saying does not apply to your project.

When you plan your project, you’re operating on a set of assumptions. And you need to make sure those assumptions are understood by everyone involved.

But maybe the idea of dealing with assumptions in project management is a bit confusing.

What are project assumptions, anyway?

How are you supposed to know what they are? And what do you do with them once you’ve identified them?

Is it worth the effort to figure it out and take the team’s valuable time to do it?

Yes. And in this post I’ll go over the following items:

• The benefit of identifying and creating a list of  project assumptions
• Different types of project assumptions – including examples
• How to identify and manage project assumptions

But first, it helps to understand just what assumptions in project management are.

What are Project Assumptions?

Project assumptions are those things you assume to be true for your project to be successful.

They’re called assumptions because you assume that for your project to move forward successfully as planned, these things will be in place.

Even though you don’t have proof at the moment, you expect them to occur during the project.

But just because you assume them to be true doesn’t mean that everyone else does. That’s why it’s important to go through the process of identifying your project assumptions.

“Just because you assume something to be true for your project doesn’t mean everyone else does. Planning around false assumptions sets you up for problems. Get it out in front of others so they can verify if it’s true or not. ”

Why It’s Important to Identify Project Assumptions

You identify and create a list of project assumptions, so you don’t have to double check everything before moving forward with your project.

You need to be able to move forward without getting bogged down checking every detail you know will likely be true.

In your day-to-day life, for example, you start each day with assumptions about what will be true:

• You assume you need a certain amount of time to get ready for and get to work each day.
• You assume that you’ll have electricity when you wake in the morning and that you’ll have hot water for your shower.
• You assume when you get in your car to drive to work, it will start.
• You assume that the train will run on time.
• You assume your office will be open and you’ll be able to conduct your work once you arrive.

These are assumptions we usually take for granted.

However, things don’t always go as planned. One day my husband walked out of the house for work, as usual. Shortly after, he walked right back in again. He was shaking his head, and said to me, “your car is on cinderblocks. Someone stole your tires.”

When I woke that morning, I assumed I’d have tires on my car so I could drive to work.

This is an extreme example (but true).

Something more likely is my assumption that traffic will flow smoothly on my drive to work. And yet I check the traffic map as I leave the house. I check that assumption so I can adjust my route if needed.

The stakes can be higher when we’re talking about the success of your project.

But many people don’t take the time to consider project assumptions. It’s easy to overlook them. After all, there are so many things to focus on, such as identifying scope, gathering requirements, creating your schedule, among many others.

Dealing with project assumptions isn’t sexy. But skipping it may come back to bite you. And if you’ve never done it, it can be confusing.

So let’s break down how to do it.

Types of Project Assumptions

To help you think through and manage assumptions, it can help to understand the different kinds of project assumptions.

They usually break out into different categories. Doing so helps you think through all the different types of assumptions you need to consider.

Here’s a list of categories to start with. If these are too many, scale back the number of categories and make them fewer and broader.

But if you’re new to project assumptions, this will help you consider the many different areas where you’ll make assumptions about your project.

• Resources – people, materials, or facilities needed to complete the project
• Delivery – what’s intended to be delivered.
• Budget – estimated cost of the project
• Finances – funding to complete the project
• Scope – the scope of the what’s to be delivered
• Schedule: tasks, durations, and dependencies needed to complete the project
• Methodology – the approach you’ll take to completing the project.
• Technology – this could cover software development , platforms, environments, and infrastructure
• Architecture and design – architecture and design approach your team will use

Now that you’ve got categories, it’s helpful to see examples.

Examples of Project Assumptions

Now that you’ve got a list of categories, it will make things even clearer to provide examples in each.

• End users will be available to test during the time they agree to
• Training rooms will be available at the training center as needed
• Project servers arrive configured as expected
• Correct number of handheld devices arrive on target delivery date with no delays
• Project costs will stay the same as initially budgeted costs
• Training will be conducted internally with no additional training costs incurred
• Funding for licenses will be provided by various departments as needed
• The project scope will not change once the stakeholders sign off on the scope statement

Another Helpful Template for you: This Simple Project Scope Statement Template Will Improve Your Project Success

• Materials will arrive as planned within the project schedule
• Vendor contracts will be fully executed within two months of vendor selection.
• Project will follow waterfall methodology throughout execution
• Project will follow team governance guidelines and requirements
• The team will write the solution in Java
• The solution will use the existing test environment
• The solution will utilize REST API architecture
• The solution will reside in an offsite cloud

If architecture is an area you’re not as familiar with, the Open Group has a great deal of information about architecture compliance that may be interesting to review.

So now…

You know what project assumptions are.

You have categories and examples.

Now you’re ready to start compiling a list of project assumptions.

How to Identify and Manage Project Assumptions

Follow these activities to address project assumptions.

1. Identify and Document

Identifying your project assumptions is not something to do all by yourself while sitting at your desk alone. You need to include the team. They’ll be able to provide insight and help create a more comprehensive project assumptions list.

Whether you do it virtually or in person, explain that you’ll be compiling the list of project assumptions with their input.

Share the categories with them and ask for ideas or feedback on them. Do they fit your project? Should they be changed in any way?

Once you’ve settled on your categories, begin to brainstorm and list the project assumptions together.

Capture them as your team shares them, and identify the category that each falls within.

As you work through these, document them.  One of the best ways to do this is in a Project Assumptions Log.

2. Create a Project Assumptions Log

The project assumptions log allows you to document additional information about your project assumptions, and track the status of each.

Simply identifying the assumptions isn’t enough. You need to document them in a way that helps everyone understand the current assumptions and how you’ll manage them going forward.

In the Project Assumptions Log include values for each of the following categories:

• Assumption log number: for ease of tracking and discussing
• Initial date logged
• Category (resource, delivery, budget, etc.)
• Name/description of the assumption
• Owner who takes responsibility for following up
• Due Date: date to validate
• Status: Open or closed
• Actions/Comments: Action needed or taken.

 3. Communicate and Validate with Stakeholders

Once you’ve got your list of project assumptions, don’t just set them aside.

Share them with stakeholders. It’s important for stakeholders to know the assumptions you’re working under.

If any of them change, it could impact your project. Your timeline or budget may change.

Additionally, your stakeholders may have insight that you’re not aware of regarding assumptions you’ve made.

If you discover any of your assumptions are wrong, make adjustments in your documentation. Make sure the team knows. The change will likely impact your plan.

You need to determine how the plan needs to change based on the new information.

Related Post: Project Communication Plan Template and Guidelines

Related Post: Increase Project Success with a Stakeholder Analysis Template

4. Monitor throughout the project

Validate your project assumptions at various points throughout the project.

Your assumption owners listed in the Project Assumptions Log should follow up and validate on the target dates.

For example, if you have an assumption about contract execution times, check with the legal or procurement team during the contract execution timeframe. Situations change, and you need to make sure your assumptions hold true throughout. As assumptions and dates pass, you can mark those items as closed.

If any project assumptions turn out to be false, this would negatively impact your project.

Monitor them throughout so that you can adjust as needed.

5. Adjust if Needed

As you monitor your project assumptions list, you may find that some assumptions change.

If they do, take action and adjust as needed.

These changes may impact your project in the areas of cost, schedule, or quality.

Be prepared to adjust your plan to account for these changes.

Communicate the changes to the team, stakeholders, and anyone else impacted.

Now you know what project assumptions are, why it’s important to identify them, and how to do it.

It may seem like a lot of work. But when you brainstorm with your team, it goes faster, and you’ll capture more than doing it alone.

It’s a great communication tool to make sure your assumptions are shared and validated, and you can monitor them throughout your project.

Use the form below to download your Project Assumptions List Template.

Capturing your project assumptions will help you communicate the situation you expect to be working within.

You also need to plan for those unexpected events that throw your project plan in a tailspin.

To help you prepare and be ready to move through them smoothly, check out How to Create a Project Management Risk Matrix

The instructions and Risk Matrix will set you up for even more success. You’ll have your team ready with response plans for events that would send others into a tailspin.

And you’re off to a great start!

About The Author

Leigh Espy is a project manager and coach with experience working in startups, government, and the corporate world. She works with project managers who want to improve their skills and grow in their career, and entrepreneurs and small businesses to help them get more done. She also remembers her early career days and loves working with new project managers and those who want to make a career move into project management.

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One of the benefits of adopting Primavera P6 over other project management tools for scheduling your projects is because Primavera P6 stores your project data in a database

Very Much Helping

Very informative and easy to understand! Thank you!

Hi Leigh, I am working in the M&E sector in Bangladesh. Your theoretical and practical knowledge really moved me. Thanks for sharing your knowledge. It has supported me greatly to understand this concept. Thanks, and hoping that more articles will come like this in future.

Working in a startup environment, knowledge and skills you impart is truly helpful.

I’m so glad you find it helpful! And thank you for your kind words!

Learning is fun with your blog It is 2:45 am in Manila, yet I cannot close my laptop.

Thank you for the kind words – I truly appreciate it!

Hi Leigh, I am studying at the UOA in Engineering Management. To be an engineering project Manager is my next career goal. Except for studies, I am wondering what I should do to enrich my experience and improve my skills for a future work opportunity? Looking forward to your reply. Thanks so much!

Kind regards, Holden

Your formal studies will help. Additionally, project work experience would be extremely beneficial. If you can manage to get work on a project, go for it. Even if you’re not the lead project manager, taking a supporting project coordinator role can also be beneficial. Even if you’re doing it through a volunteer organization it can be valuable. Not only will you get the project experience on your resume, you’ll be able to make connections that could be helpful, too. Best of luck to you!

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How to Write Assumptions for a Thesis

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