example of assumption in research paper

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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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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Questions to Ask While Writing a Research Paper

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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.
• << Previous: Inferences
• Next: Implications >>
• Last Updated: Jul 10, 2023 11:50 AM
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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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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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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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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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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

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

Glafera Janet Matanguihan

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

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

INTRODUCTION

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

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

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

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

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

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

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

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

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

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

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

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

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

Research questions in quantitative research

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

Hypotheses in quantitative research

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

Research questions in qualitative research

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

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

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

Hypotheses in qualitative research

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

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

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

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

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

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

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

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

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

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

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

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

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

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

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

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

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

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

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

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

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

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

Author Contributions:

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

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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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How to Write Assumptions for a Thesis

Related Papers

JASH MATHEW , MAURICE MUKINGINYI WEKESA

The purpose of the study was to analyze the determinants of effective fraud management in domestic tier one commercial banks in Trans Nzoia County. The analysis was focused on the domestic tier one commercial banks in the County as the population of the study. The study was guided by the following objectives; to analyze the effect of the independence of the internal audit personnel, the competence of the internal audit personnel, the presence of the internal audit charter and the management support as determinants of effective fraud management in the d0mestic tier one commercial banks. The study was guided by the agency theory, the fraud management lifecycle/theory and the communication theory. A correlation research design was adopted in which an in-depth study of the determinants of effective fraud management was carried out from the target population of the senior management staff and the internal audit personnel in the domestic tier one commercial banks in the County. The survey targeted departmental heads in the banks by employing census method. The source of the required data was through the questionnaires, covering both qualitative and quantitative data, administered to the target population by the researcher. The questionnaire was designed for data collection and eventual analysis by both the regression tools and ANOVA using the Statistical Package for Social Sciences (SPSS) version 22. A multiple correlation coefficient and regression analysis together with the ANOVA test were carried out to establish the relationship between the independent variables and dependent variable. The findings revealed that the regression effect is statistically significant and indicated an accomplished prediction of the dependent variable, better than if done through chance through the F calculated (F =12.2896) which was greater than 5% level of significance that showed the overall model was significant where the Internal Audit Independence explained 11% of EFM, Competence of Internal Auditor Personnel 46% of EFM, Presence of Internal Audit Charter 12% of EFM, and Management Support explained 16% of EFM within the domestic tier one commercial banks. However, Competence of Internal Audit Personnel was the most significant predictor (determinant) of EFM at 46% with (β=0.086). The results are expected to contribute to the existing body of knowledge for the crucial role of internal audit function in the banking industry as well as forming a basis for scholars who may want to study issues related to effective fraud management in the banking sector. They are further expected to help in revealing key issues that help improve the success of internal audit section within commercial banks, and also help unearth the fundamental issues related to Internal Audit management in the banking sector.

JIBISM JOURNALS

The main objective of the study was to determine the influence of organizational restructuring on employee job satisfaction in selected commercial banks in Kenya. The study was guided by the following specific objectives; to establish the influence of downsizing, centralization, downscoping and business process reengineering on employee job satisfaction in selected commercial banks in Kenya. The study used stratified random sampling to select the sample 230 of employees at Kenya Commercial Bank and National Bank headquarters. Primary data was collected by using questionnaires. Data was analyzed using Statistical Package for Social Sciences (SPSS). Correlation analysis was used to establish whether there is a relationship between the dependent and independent variable. Multiple regression analysis was used to show the weight of the relationship between the independent and dependent variables. The study established that downsizing had a significant negative relationship with employee job satisfaction in selected commercial banks in Kenya; centralization had a significant positive relationship with employee job satisfaction in selected commercial banks in Kenya; down scoping had a significant positive relationship and business Process reengineering had a significant positive relationship with employee job satisfaction in selected commercial banks in Kenya.

Ethel Chogawana

The objective of the research was to establish the Effect of Internal Controls on Financial Performance of Commercial Banks in Kenya. Internal Controls were measured using the five elements of internal control as stipulated by the Committee of Sponsoring organizations of Treadway Commission framework of internal controls while Financial Performance was measured using the historical average of Return on Equity. A descriptive research design was adopted due to its ability to describe the relationship between elements of Internal Controls and Financial Performance. The study used the 43 commercial banks in Kenya. Primary data was collected using a structured questionnaire. Descriptive statistics obtained from data analysis were presented using frequency tables, while inferential data findings were presented using correlation and regression tables. The study findings revealed that the banking sector enjoys a strong financial performance partly because of implementing and maintaining effective internal controls. The existence of effective internal control is attributed to the highly regulated and structured environment in the banking sector. The study recommends banks should effectively implement and maintain internal controls due to the nature of the riskiness of the banking sector and its impact on financial performance.

IOSR Journals

Most public institutions of higher learning across the world have reported suboptimal financial performance compared to private institutions of higher learning. The poor financial performance can be attributed to financial management practice. The sound financial management practices require the institutions of robust internal control systems. However, there are limited empirical research findings regarding the relationship between the internal control system and financial performance. The specific objectives of the study were: to determine the effect of control activities, risk assessment, control environment, information and communication and monitoring on financial performance of institutions of higher learning in Vihiga County, Kenya. The study was anchored on agency theory, stewardship theory, positive accounting theory and attribution theory. The study used a descriptive research design. The target population of respondents was 140 employees in the four institutions studied whereas the sample size was 96 employees. Primary data was collected from sample population using semi-structured questionnaires. Descriptive and multiple regression analysis were used to analyze data. The study found that the institutions had adequate and effective control activities which included regular internal audit reports, adequate segregation of duties in the finance and accounts departments and physical controls to prevent excess allocated funds. Control activities were found to have a positive significant effect on the financial performance of the institutions under study. The study found that the institutions under study had proper risk assessment tools and risk assessment management system because they carried out continuous financial assessment of their organizations coupled with regular, timely and profound audits. Risk assessment was found to have a positive significant effect on the financial performance of the institutions under study. The study established that the institutions had effective control environment. The number of staff in finance and audit departments was adequate and well trained on accounting and financial management system. Control environment was found to have a positive and significant effect on the financial performance of the institutions under study. The study found that the institutions had effective flow of information and communication channels. In addition, the study found that effective flow of information and communication enhanced financial accountability and financial performance of the institutions. The expenditure of the institutions was properly monitored and audit departments were independent. Financial monitoring was found to have a positive and significant effect on the financial performance of the institutions under study. To the management of the public institutions of higher learning, the study recommends regular and timely financial audit to help them identify any loop holes in their financial systems as well as financial performance.

wafula Mang'eni

Before the introduction of micro prudential regulations, some banks experienced delinquency issues that really put to risk customers " funds and raised customer exploitation concerns. With the introduction of bank specific guidelines by the bank regulatory authorities, some banks faced liquidation risks because of adverse effects of stringent micro prudential regulations, thus making micro prudential regulations an intolerable monster in the banking industry. The objective of this study was to establish if there is a relationship between bank specific guidelines and financial performance of Commercial Banks in Kenya. The study adopted a descriptive research design. The population of study was 95 top management employees in the 19 branches of Kenya Commercial Banks in Nairobi County and the period of study was from 2010 to 2017. The study mainly used primary data. A linear regression model of financial performance versus regulations was then applied to examine the effect of banking regulations on financial performance of commercial banks in Kenya. The study findings indicated that there is a positive and significant effect of loan management policies (Beta = 0.478, Sig = 0.000), liquidity management (Beta = 0.243, Sig = 0.000), capital adequacy (Beta = 0.324, Sig = 0.000) and management quality (Beta = 0.461, Sig = 0.008) on financial performance of commercial banks in Kenya. However, asset quality does not have a significant effect on financial performance of commercial banks in Kenya (Beta = 0.101, Sig = 0.362). The study concluded that favorable bank specific regulations can positively improve the performance of commercial banks in Kenya. The study recommends commercial banks to come up with better policies to cope with the central bank of Kenya bank specific regulations in order to improve their performance.

International Journal of Academics & Research, IJARKE Journals

In the recent past the Kenyan banks have experienced a number of corporate failures related to transparency and accountability, their attention was focused on corporate governance matters instead of risk based audit. In 2016, Chase bank, Dubai bank and Imperial bank was positioned under financial management statutory due to suspicions of money laundering and fraud. The purpose of this study was the analysis of risk maturity assessment on audit quality of Tier I commercial banks in Kenya. Specifically to establish the influence of periodic risk audit planning on audit quality; to establish the influence of individual audit assignment on audit quality of tier I commercial banks in Kenya. Descriptive research design was adopted. The study targeted a population of 1597 staffs who constituted respondents from, accounting and finance, internal audit and Risk and compliance department of tier I commercial banks in Kenya. Stratified random sampling was used to select a sample of 104 respondents. Structured questionnaire was used to collect data. Data was analysed by use of inferential and descriptive statistics. Tables was used for data presentation since it is to understand and internalize data and primary data was used. Pilot study was conducted in tier two commercial banks in head office, Nairobi. The internal consistency was tested by use of Cronbach (Alpha – α) model with the alpha coefficient of above 0.7 being considered reliable. Multiple regression analysis was used to determine the strength and direction of the relationship between the independent variables and the dependent variables. These correlations were further subjected to significance test to determine whether the observed correlations were significant. A significance level of 0.05 was therefore set for testing the research hypotheses. The study revealed that Risk Maturity Assessment had the highest coefficient, Beta = 0.261, followed by Periodic risk audit planning with Beta = 0.207 and lastly Individual audit assignment with Beta = 0.174; this indicates that Risk Maturity Assessment makes the strongest unique contribution in explaining the quality of audit in Tier I Commercial Banks in Kenya, Periodic risk audit planning had the second largest unique contribution while Individual audit assignment had the least unique contribution in explaining the variation in the quality of audit in Tier I Commercial Banks in Kenya, Periodic risk audit planning. Among the three predictor variables, Risk Maturity Assessment was found to be the strongest predictor of the quality of audit in Tier I Commercial Banks in Kenya, followed by Periodic risk audit planning risk planning, and lastly Individual audit assignment. The study findings are expected to be of value to the banks stakeholders and form a basis for improving audit quality of banks by enhancing risk based audit. The study concludes that risk based auditing through risk assessment, Periodic risk based planning and individual audit assignment should be enhanced. This would enable the commercial banks to be able to detect risks on time and concentrate on high risk areas leading to increased transparency and accountability, hence enhancing financial performance and audit quality. The study recommends that management in commercial banks in Kenya should adopt effective risk based audit practices such as risk assessment, periodic risk based planning and individual audit assignment to enhance effective and efficient audit reports.The study recommends that the management of commercial banks should consider risk based audit in auditing process and risk management.

khalid uddin

IJSSIT Publication

Iasir Journals

The objective of the study was to establish the adequacy of existing cash control system and its effect on the performance of banks in Kenya. The study used descriptive survey as a research design. The target population of this study comprised of 60 respondents drawn from ten commercial banks in Eldoret town, Uasin Gishu County. Data was collected by use of questionnaires and analyzed in excel spreadsheets then presented in tables. The study findings showed that adequacy of exiting internal control system improves performance of the firm. The study recommended that, management of banking sector should involve all the stakeholders that is employees in the organization while carrying out internal control so as to improve its adequacy for the organization and oversee its projected profits. The organization should also benchmark from other successful organization with successful internal control system

Ojo A D U R A G B E M I Sunday

This research examined the effect of internal audit in financial performance of commercial bank, a case study of United Bank for Africa. Specifically, the study detect the level of practice and internal audit function in the commercial banks operating in Nigeria, it identify the level of improvement in the financial performance of commercial banks operating in Nigeria and finally it improve the financial performance of commercial banks operating in Nigeria,. Both primary and secondary sources of data were adhered to on the course of this study and the attitude and responses of those interviewed were noted. The sample size for this study is fifty (50) staff of First Bank Nigeria Plc. Data was obtained through questionnaire and oral interviews. The data that will be collected from various sources, will be analyze using the following statistical measurement are simple percentage and chi-square (X2). The study also reveals that frauds are identified by the internal audit function. Findings show that the standard for audits and audit-related services influence the performance of commercial banks. Finally findings show that there is financial performance of commercial banks operating in Nigeria. It was recommended that the salaries department should keep a history record of engagement, retirement or dismissal, salaries and deduction of each employee.

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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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Example Of Assumption In Quantitative Research

The sample paper on Example Of Assumption In Quantitative Research familiarizes the reader with the topic-related facts, theories and approaches. Scroll down to read the entire paper.

Post-positivism allows researchers to examine realities through a variety of measurement tools; thus accessing realities which could elude measurement by direct observation (Giddings & Grant, 2007; Schumacher & Greener, 1992). Regardless of whether the researcher adopts a positivist or post-positivist philosophy, the description of the paradigms begin with assumptions about the researcher’s role and relationship to the setting, and by identifying the epistemological and validity assumptions underlying the choice of the role and relationship.

The conviction that there is a reality existing outside of the researcher, hat this reality can be observed (ontology), and that knowledge of this reality can be measured objectively (epistemology) are foundational assumptions in quantitative research (Hathaway, 1995). Thus the objects of interest are measured by instruments (e. G. , telescope), the data is examined and analyzed to determine if logical patterns are present, and rational theories are constructed to explain and predict a variety of facts (Hathaway, 1995).

Ontologically the researcher assumes that the external reality is comprised of facts that are “law-like” and provide structure or a theoretical framework to this reality. Physics provides an example of this approach.

Methodological and Ontological Assumptions

Writing assumptions in research.

Empirical-analytical inquiry is characterized by the researcher’s detached or objective view from the setting under study. This objectivity or detachment is, in part, due to the assumption that the object under study is separate from or independent of the researcher (Eisner, 1981; Smith, AAA; Smith, Bibb).

Proficient in: Data

“ She followed all my directions. It was really easy to contact her and respond very fast as well. ”

In the empirical analytical view, researchers adhere to the mind-reality duality and the mind is seen as separate from reality (Hathaway, 1995). Another way of considering objectivity is that of being hurry neutral (Schumacher & Greener, 1992). This is an extreme view and within the contemporary empirical analytical view, researchers would claim that most inquiry is theory laden (Smith, Bibb).

However, with objectivity as the goal, the researcher strives to prevent biases throughout the research process and attempts to control the research design for validity, credibility, and reliability (Burns & Grove, 1997). While it is impossible to achieve complete objectivity, cultivating an awareness of potential threats and taking measures to decrease threats whenever possible serves to strengthen the research project. It is important to underscore the intertwined nature of the assumption about objectivity and the assumption that a reality exists outside of the observer. The observer, or researcher, assumes that reality exists outside of the human experience (Carroty, 1998; Polite-O’Hara et al. , 1991).

In other words, there are facts with an objective reality separate from the beliefs of the researcher therefore reality exists regardless of the researcher’s presence (Firestone, 1987). In a contemporary perspective, reality holds a mediated position between the objective and subjective worlds. Reality affects human beings and unman beings effect reality (Schumacher & Greener, 1992). Thus unobservable realities exist and can be represented in theoretical concepts. This line of thinking extends teen assumption AT realty Deanna Tanat wanly can De crossover only Dye slung the senses.

An example of an unobservable reality would be a belief that depression is a reality. Depression is not an object that we can observe. Rather we can observe phenomena such as actions, behaviors, and consequences that may be associated with depression. Given this phenomenon, theoretical Judgments are made about what constitutes a theoretical reality of depression. The theoretical construct enables the researcher to design a research project on the subject of depression.

Linked to the assumption about reality is the assumption that reality consists of facts or truths that can be known (Hathaway, 1995) and these facts provide the researcher with a theoretical framework to help guide the inquiry (Firestone, 1987). The researcher aims to precisely and define categories based on these facts before the study begins and then determines the relationships between them (Firestone, 1987; Smith, Bibb). Hypotheses establishing a relationship between cause and effect are rived from these categories and only the data that is relevant to them are collected and tested.

An extreme critique may be that reality is being actively structured by the researcher’s prosecuted categories and that this methodology is unduly controlled regarding what is relevant to the study. The assumption underlying this point is the deterministic or linear nature of hypothesis testing. Control is inherent in this method of inquiry which is another underlying assumption of quantitative research. Researchers using a more moderate approach within the post positivist paradigm recognize that research is a human endeavor.

They derive their a priori categories from personal beliefs or experience, from theoretical formulation, or from their own or others interpretive research (Hathaway, 1995). Because reality is considered to be relatively stable and researchers are able to observe it, a further assumption is that of objective measurement (Polite-O’Hara et al. , 1991). The purpose of objective measurement is to gain an understanding about the reality of a phenomenon in an objective manner (Giddings & Grant, 2007). Thus, in the act of documenting and measuring, the researcher, in the role of a detached onlooker, reserves objectivity (Hathaway, 1995).

In other words, it is essential that the measurement tool(s) and process are objective to gain closer proximity to true knowledge of the phenomenon. Measurement is an important assumption in quantitative research and measurement tools, if properly designed and applied, can lead the researcher to greater understanding about the phenomenon. Measurement is the process of assigning numbers to the phenomenon using some type of rule (Burns & Grove, 1997). Before assigning numbers there is an assumption that the measurement tool(s) will be accurate in measuring the phenomenon.

For example, if a researcher wants to measure pain, a measurement tool such as a pain scale could be used. Alternatively, the researcher could choose to measure opinions about various pain treatments. In order to measure the opinions, the researcher would assign numbers to the most likely responses observed. In constructing the pain treatment opinion tool(s), it is essential that the measurement tool(s) have an appropriate correspondence to the reality of pain treatment opinions (Polite-O’Hara et al. , 1991). Thus to accurately measure a phenomenon, the measurement tool(s) must be based on a reality and be as objective as possible.

The assumptions of reality, objectivity and measurement are interrelated and integral to the ontology and methodology AT quant I t tattle research. I nose assumptions are essential components in the design of quantitative research projects. An example is if the researcher seeks to understand philosophies of childhood, their assumptions about reality, objectivity, and measurement related to this philosophy are embedded in the designing the research project. There is an assumption that a reality about philosophies of childhood exist.

Additionally, there are assumptions that philosophies of childhood can be measured and done so objectively. The researcher would consider how to objectively measure philosophies of childhood when developing the research design. If there were no existing tool(s) to measure the reality of philosophies of childhood, it would be necessary to develop a measurement tool(s) which could accurately measure the phenomenon. In developing the tool, the researcher would make objective theoretical Judgments about what variables (e. G. , psychological, biological, etc. ) would signify this phenomenon.

In sum, assumptions that the reality (philosophies of childhood) exists, that such realities are measurable, and that the assortment and process of inquiry are as objective as possible are hallmarks in the quantitative approach to research. Epistemological Assumptions Knowledge within the empirical analytical paradigm has utility if it is generalized. The aim of inquiry is to generalize from the particular and apply a theoretical framework that can be applied universally (Hathaway, 1995). Therefore the aim of generalization is served by the development of universal knowledge.

A broad example is research on the efficacy of pain medications. Control and experimental groups are observed to determine the effects of a specific drug. If there is justification to believe it alleviates pain the medication is made available for treating the population at large through a regulated process. Knowledge is also defined by what researchers call data and the selection of meaning. The researcher conducting empirical analytical inquiry makes decisions that will reveal what is generally applicable to all similar situations (Firestone, 1987; Smith, AAA; Smith, Bibb).

Taking a critical stance, Habeas (1971) claimed that such inquiry implies a dissociation of knowledge from human interest (Habeas, 2005) and questions the it with individual contexts, values, and preferences. Caution must be taken when considering that the context of discovery may be quite different than the context of practice. Separating the universal from the particular is accomplished through several processes (e. G. , instrumentation and precision) and methodological assumptions (e. G. , measurement techniques) (Hathaway, 1995).

The researcher, independent of specific situations under study, determines a set of hypothesized categories based on a priori knowledge and conducts a controlled inquiry to give meaning to phenomena that have significance at a generalized level. Data are considered factual or context-free when they have the same meaning across situations and settings (Hathaway, 1995).

The decisions researchers make concerning research methods have a direct impact on how they make meaning of their world. By adopting quantitative research, reality is structured and understood in a particular way. In some ways, the choice of quantitative approaches creates the reality we are attempting to discover.

By making a choice to conduct quantitative inquiry, we choose our paradigm or assumptions auto teen world (Leaner, BIBB; Hathaway, 1 Assumptions Tanat a realty exalts operate from the researcher, that such realities are measurable, and that the measurement and process of inquiry are as objective as possible are hallmarks of quantitative research. References Lender, J. S. (1986). Educational research: A personal and social process.

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