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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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What is Hypothesis?
We have heard of many hypotheses which have led to great inventions in science. Assumptions that are made on the basis of some evidence are known as hypotheses. In this article, let us learn in detail about the hypothesis and the type of hypothesis with examples.
A hypothesis is an assumption that is made based on some evidence. This is the initial point of any investigation that translates the research questions into predictions. It includes components like variables, population and the relation between the variables. A research hypothesis is a hypothesis that is used to test the relationship between two or more variables.
Characteristics of Hypothesis
Following are the characteristics of the hypothesis:
- The hypothesis should be clear and precise to consider it to be reliable.
- If the hypothesis is a relational hypothesis, then it should be stating the relationship between variables.
- The hypothesis must be specific and should have scope for conducting more tests.
- The way of explanation of the hypothesis must be very simple and it should also be understood that the simplicity of the hypothesis is not related to its significance.
Sources of Hypothesis
Following are the sources of hypothesis:
- The resemblance between the phenomenon.
- Observations from past studies, present-day experiences and from the competitors.
- Scientific theories.
- General patterns that influence the thinking process of people.
Types of Hypothesis
There are six forms of hypothesis and they are:
- Simple hypothesis
- Complex hypothesis
- Directional hypothesis
- Non-directional hypothesis
- Null hypothesis
- Associative and casual hypothesis
Simple Hypothesis
It shows a relationship between one dependent variable and a single independent variable. For example – If you eat more vegetables, you will lose weight faster. Here, eating more vegetables is an independent variable, while losing weight is the dependent variable.
Complex Hypothesis
It shows the relationship between two or more dependent variables and two or more independent variables. Eating more vegetables and fruits leads to weight loss, glowing skin, and reduces the risk of many diseases such as heart disease.
Directional Hypothesis
It shows how a researcher is intellectual and committed to a particular outcome. The relationship between the variables can also predict its nature. For example- children aged four years eating proper food over a five-year period are having higher IQ levels than children not having a proper meal. This shows the effect and direction of the effect.
Non-directional Hypothesis
It is used when there is no theory involved. It is a statement that a relationship exists between two variables, without predicting the exact nature (direction) of the relationship.
Null Hypothesis
It provides a statement which is contrary to the hypothesis. It’s a negative statement, and there is no relationship between independent and dependent variables. The symbol is denoted by “H O ”.
Associative and Causal Hypothesis
Associative hypothesis occurs when there is a change in one variable resulting in a change in the other variable. Whereas, the causal hypothesis proposes a cause and effect interaction between two or more variables.
Examples of Hypothesis
Following are the examples of hypotheses based on their types:
- Consumption of sugary drinks every day leads to obesity is an example of a simple hypothesis.
- All lilies have the same number of petals is an example of a null hypothesis.
- If a person gets 7 hours of sleep, then he will feel less fatigue than if he sleeps less. It is an example of a directional hypothesis.
Functions of Hypothesis
Following are the functions performed by the hypothesis:
- Hypothesis helps in making an observation and experiments possible.
- It becomes the start point for the investigation.
- Hypothesis helps in verifying the observations.
- It helps in directing the inquiries in the right direction.
How will Hypothesis help in the Scientific Method?
Researchers use hypotheses to put down their thoughts directing how the experiment would take place. Following are the steps that are involved in the scientific method:
- Formation of question
- Doing background research
- Creation of hypothesis
- Designing an experiment
- Collection of data
- Result analysis
- Summarizing the experiment
- Communicating the results
Frequently Asked Questions – FAQs
What is hypothesis.
A hypothesis is an assumption made based on some evidence.
Give an example of simple hypothesis?
What are the types of hypothesis.
Types of hypothesis are:
- Associative and Casual hypothesis
State true or false: Hypothesis is the initial point of any investigation that translates the research questions into a prediction.
Define complex hypothesis..
A complex hypothesis shows the relationship between two or more dependent variables and two or more independent variables.

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Types of Research Hypotheses

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Research Hypothesis: Definition, Types, & Examples
Saul Mcleod, PhD
Educator, Researcher
BSc (Hons) Psychology, MRes, PhD, University of Manchester
Saul Mcleod, Ph.D., is a qualified psychology teacher with over 18 years experience of working in further and higher education.
Learn about our Editorial Process
Olivia Guy-Evans
Associate Editor for Simply Psychology
BSc (Hons), Psychology, MSc, Psychology of Education
Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.
A hypothesis (plural hypotheses) is a precise, testable statement of what the researcher(s) predict will be the outcome of the study. It is stated at the start of the study.
This usually involves proposing a possible relationship between two variables: the independent variable (what the researcher changes) and the dependent variable (what the research measures).
In research, there is a convention that the hypothesis is written in two forms, the null hypothesis, and the alternative hypothesis (called the experimental hypothesis when the method of investigation is an experiment ).
A fundamental requirement of a hypothesis is that is can be tested against reality, and can then be supported or rejected.
To test a hypothesis the researcher first assumes that there is no difference between populations from which they are taken. This is known as the null hypothesis. The research hypothesis is often called the alternative hypothesis.
In This Article
Types of research hypotheses
Alternative hypothesis.
The alternative hypothesis states that there is a relationship between the two variables being studied (one variable has an effect on the other).
An experimental hypothesis predicts what change(s) will take place in the dependent variable when the independent variable is manipulated.
It states that the results are not due to chance and that they are significant in terms of supporting the theory being investigated.
Null Hypothesis
The null hypothesis states that there is no relationship between the two variables being studied (one variable does not affect the other). There will be no changes in the dependent variable due to the manipulation of the independent variable.
It states results are due to chance and are not significant in terms of supporting the idea being investigated.
Nondirectional Hypothesis
A non-directional (two-tailed) hypothesis predicts that the independent variable will have an effect on the dependent variable, but the direction of the effect is not specified. It just states that there will be a difference.
E.g., there will be a difference in how many numbers are correctly recalled by children and adults.
Directional Hypothesis
A directional (one-tailed) hypothesis predicts the nature of the effect of the independent variable on the dependent variable. It predicts in which direction the change will take place. (i.e. greater, smaller, less, more)
E.g., adults will correctly recall more words than children.

Falsifiability
The Falsification Principle, proposed by Karl Popper , is a way of demarcating science from non-science. It suggests that for a theory to be considered scientific it must be able to be tested and conceivably proven false.
However many confirming instances there are for a theory, it only takes one counter observation to falsify it. For example, the hypothesis that “all swans are white,” can be falsified by observing a black swan.
For Popper, science should attempt to disprove a theory, rather than attempt to continually support theoretical hypotheses.
Can a hypothesis be proven?
Upon analysis of the results, an alternative hypothesis can be rejected or supported, but it can never be proven to be correct. We must avoid any reference to results proving a theory as this implies 100% certainty, and there is always a chance that evidence may exist which could refute a theory.
How to write a hypothesis
- 1. To write the alternative and null hypotheses for an investigation, you need to identify the key variables in the study.The independent variable is manipulated by the researcher and the dependent variable is the outcome which is measured.
- 2. Operationalized the variables being investigated.Operationalisation of a hypothesis refers to the process of making the variables physically measurable or testable, e.g. if you are about to study aggression you might count the number of punches given by participants
- 3. Decide on a direction for your prediction. If there is evidence in the literature to support a specific effect on the independent variable on the dependent variable, write a directional (one-tailed) hypothesis.If there are limited or ambiguous findings in the literature regarding the effect of the independent variable on the dependent variable, write a non-directional (two-tailed) hypothesis.
- 4. Write your hypothesis. A good hypothesis is short (i.e. concise) and comprises clear and simple language.
What are examples of a hypothesis?
Let’s consider a hypothesis that many teachers might subscribe to: that students work better on Monday morning than they do on a Friday afternoon (IV=Day, DV=Standard of work).
Now, if we decide to study this by giving the same group of students a lesson on a Monday morning and on a Friday afternoon and then measuring their immediate recall on the material covered in each session we would end up with the following:
- The alternative hypothesis states that students will recall significantly more information on a Monday morning than on a Friday afternoon.
- The null hypothesis states that there will be no significant difference in the amount recalled on a Monday morning compared to a Friday afternoon. Any difference will be due to chance or confounding factors.
The null hypothesis is, therefore, the opposite of the alternative hypothesis in that it states that there will be no change in behavior.
At this point, you might be asking why we seem so interested in the null hypothesis. Surely the alternative (or experimental) hypothesis is more important?
Well, yes it is. However, we can never 100% prove the alternative hypothesis. What we do instead is see if we can disprove, or reject, the null hypothesis.
If we reject the null hypothesis, this doesn’t really mean that our alternative hypothesis is correct – but it does provide support for the alternative / experimental hypothesis.
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- What Are The Types of Research Hypothesis? + [Examples]

It is vital to fully understand a hypothesis to address the types of research hypotheses. A hypothesis explains an established or known fact that has not yet been proven or validated.
Simply put, it is a statement explaining why and how a particular thing works based on philosophical assumptions and facts.
For example, a hypothesis goes like this;
A patient is likely to trust the pediatrician’s diagnosis based on the perception that the doctor is well-versed in the practice of medicine.
A hypothesis is a basis for scientific research or experiment, usually coined as a research hypothesis.
Three attributes or features measure the viability of a research hypothesis, and they are as follows.
- A research hypothesis must be specific, testable or measurable, and verifiable. In other words, the research hypothesis should create clear predictions than can be tested.
- Ideally, a hypothesis can be drawn from previous theoretical research publications.
- A good research hypothesis is much more than an intelligent guess, and sometimes, a research hypothesis could take the form of research questions that can be explored further via research and suggest an expected result.
Research hypotheses are a vital part of the scientific process that leads to or are the reasons for scientific experiments. That said, a slight flaw in constructing a hypothesis could generate negative results.
There are various types of hypotheses, and the following checklist should guide a good hypothesis.
- Is the language employed clear and direct?
- Is there a good relationship between the hypothesis and the research topic?
- Can the hypothesis be tested?
- What are the methods used to carry out testability?
- What are areas of explanation being addressed?
The essence of this checklist is to get your hypothesis up on the right footing and help you pinpoint any gaps or weaknesses.
The following listed below are the various 7 types of research hypotheses.
1. Simple Hypothesis
It can show the impact of a relationship between a single dependent variable and a single independent variable. For example,
Consuming too many fizzy drinks will cause weight gain and a bloated belly.
2. Complex Hypothesis
It foretells the relationship between multiple independent and dependent variables.
For instance, eating more vegetables and a low-calorie diet would lead to weight loss.
3. Directional Hypothesis
It shows the expected direction required to determine the relationship between variables and is derived from theory. Furthermore, it shows a researcher’s intellectual commitment to a particular outcome by the length of the study.
For example,
Toddlers under the age of 4 who were given well-balanced meals for 5 years showed a higher IQ level than their counterparts who did not have the same treatments.
4. Non-directional Hypothesis
It does not predict the direction or nature of the relationship between the two variables. A non-directional hypothesis is used mostly when there is no theory involved. For example, men and women differ in terms of helpfulness.
5. Associative and Causal Hypothesis
The associative hypothesis shows the interdependency between related variables. A change in one variable results will cause a change in the other variable. However, the change is not caused by either of the variables.
For example, the increase in the number of unhealthy people visiting a particular hospital is not because the hospital is the source of their illness. Rather it could be a result of other unrelated factors like the weather, personal hygiene practices, etc.
On the other hand, the causal hypothesis predicts the effect a change in variables would have on different variables. For instance, a change in the writing style on their blog led to higher user engagement.
6. Null Hypothesis
This refers to a lack of relationship between different variables. For example, plants would grow irrespective of the source of water, natural or artificial. It proposes a negative statement to support the researcher’s discovery, showing that no relationship exists between the two variables.
7. Alternative Hypothesis
The alternative hypothesis is a statement used in statistical experiments. It is the opposite of the null hypothesis and is described by the term H1 or Ha. The term alternative is used because it is the alternative to the null hypothesis. Therefore it is safe to say that it is an alternative theory to the one a researcher is testing and trying to prove.
The Alternative Hypothesis is classified into two categories;
Directional and Non-Directional.
- Directional: A statement outlining the ways the expected outcomes would be collated. It is mostly used in cases where there is a need to establish a relationship between two different things or when comparing various groups. For example, Attending physiotherapy sessions will improve the stage performance of ballerinas.
- Non-directional: This implies no direction for the expected results. For example, attending physiotherapy sessions impacts the stage performance of ballerinas.
The directional statement clearly states that the physiotherapy sessions would boost performance in both examples outlined above. At the same time, the non-directional only acknowledges that the sessions would influence performance without stating whether the influence would be positive or negative.
8. Empirical Hypothesis
When a theory is proven through an experiment and observation, this justifies or validates a claim and distinguishes it from a wild guess.
Here are a few examples that depict the empirical hypothesis:
a. Women who take folate supplements face a lesser risk of having children with congenital disabilities.
b. Good behavior in children can be reinforced when they are rewarded for good behavior.

9. Statistical Hypothesis
It is a statement that postulates a theory based on studying a sample population. It is a logic-based analysis where a specific population is researched to gather evidence to prove a particular theory.
For example:
43% of the American population in the age group of 22-29 speak a second language.
Importance of a Testable Hypothesis
Testability in the hypothesis is crucial in establishing any scientific research in the physical world. This is because research or any science founded on a hypothesis is usually laced with inherent flaws. One of the flaws is the idea that any hypothesis by design significantly reduces the area of exploration, which births experimental results that would fail in real-life scenarios.
This problem is further compounded by modern science, which equates philosophical concepts to physical science. Testability solves these problems by making the research hypothesis more truthful, based on real tenable results. Hence any well-thought-out hypothesis would be founded in testability.
The condition for any viable hypothesis is testability. To be considered testable, the following criteria must be fulfilled.
- There must exist a viable means to prove that the hypothesis is true.
- Similarly, there must be a possibility to prove the hypothesis false.
- Finally, the result of the hypothesis must be replicable.
Without these testability criteria, the hypothesis and proposed results would be indefinite, and the significance of the experiment would be lost.
How To Formulate an Effective Research Hypothesis
There are clear and precise steps to creating an effective research hypothesis. An effective research hypothesis must answer these 6 questions;
What, who, where, when, how, and why?.
In the scientific method, the first step is to ask a question. Frame this question using the classic six highlighted above. For example:
- How long does it take avocados to grow?
- Why do we have shorter days and longer nights in winter?
- What happened to the groundnut pyramids?
- How does a caterpillar become a butterfly?
- Why are students excited on Friday afternoon?
- How does sleep affect motivation?
- Why do tax systems help build an economy?
So the first step is to identify and state what problem you are trying to solve. The hypothesis must clearly define the subject, the experiment’s focus, and the expected outcome.
Put together preliminary research data from a wide range of sources, including academic journals, personal experiments, and observations from the work of others. Afterward, define the variables, and separate the dependent variables from the independent variables.
The independent variables are the ones that are malleable and can be tweaked, controlled, changed, and affected by various conditions. Secondly, independent variables are isolated from other factors of the research.
On the other hand, dependent variables rely on other aspects of the research and are affected by any change in the independent variable.
Refine your hypothesis by emulating the following as a checklist:
- Specific language devoid of any ambiguity must be used.
- Clearly predict the relationship between the variables and the expected outcome.
- No prior assumptions should be made about the reader’s knowledge.
- The results must be testable, relevant, and specific to the research questions.
However, one of the proven methods of determining the effectiveness of your research hypothesis is to compare it to an already-existing hypothesis. It would help guide and make the process easier.
Here are a few general examples that can guide you in formulating your hypothesis:
a. Eating a generous amount of fiber-rich fruits like apples after age 50 would keep the doctor away or limit visits to the doctor’s office.
b. Cheap airlines, referred to as budget airlines, will receive more customer complaints than regular or premium airlines because of the limited amenities provided compared to full-service airlines.
Stating the obvious, the final step is to write your hypothesis using all the steps outlined. It is important to remember that your hypothesis is a statement that shows who or what is being studied, the variables, and your predicted outcome.
Hypothesis in Research
We have already established that a hypothesis is an idea or a statement based on tangible evidence that can be proven. A hypothesis in research is simply a statement concerning the predicted outcome of a scientific study. In this instance, it has to be specific, testable, and falsifiable.
Specific here refers to clarity about the parties involved and the expected results.
For example, a patient’s perception of a doctor’s experience breeds a higher level of trust in the doctor’s diagnosis.
This example depicts the clarity and directness of the subject. There is no ambiguity in the expectations of the relationship referred to.
Testability in research hypothesis is simply saying that the hypothesis must be provable. This means that the data gathered must be collected and observed in a thorough scientific process to assess the quality of the hypothesis. In other words, there must be a proven way to validate the claims of the hypothesis.
For example, the doctor referred to in the previous hypothesis can be validated by other patients’ perceptions of his competence and previous results from past diagnoses. A quantitative research approach using a large number of people would have been used to test the claims of this hypothesis.
The falsifiability in the research hypothesis means that the hypothesis can be refuted. This step is essential in validating or establishing the viability of the hypothesis. Hence there has to be an emphatic way of confirming if a hypothesis is false.
The claim is that life exists on planets like the earth. This claim cannot be a hypothesis because the only way to verify this would be to visit all planets in the world and come back with evidence of life. This claim is not disprovable.
So when conducting a hypothesis in research, it is vital to meet all these criteria to have an effective hypothesis.
Hypothesis in Statistics
A hypothesis in statistics is a legal claim about a subject within the framework of a statistical model. It is a process of statistical inference to determine if the data collated is inadequate to prove a hypothesis. The data used here can be gleaned from a large population. A statistical analyst verifies a hypothesis by analyzing a random sample of the population.
In this case, the random population sample is used to test 2 different hypotheses; the null hypothesis and the alternative hypothesis.
4 Steps of Statistical Hypothesis Testing
There is a four-step process used for statistical hypothesis testing.
- State only two hypotheses; that way, only one can be right.
- Create an analysis plan that shows how the data would be evaluated.
- Implement the plan by physically analyzing the sample data
- Analyze the result and either accept the hypothesis or state the plausible hypothesis based on the given data.
For example, if you want to carry a test on, say, 50% of exceptional college students come from wealthy homes.
The null hypothesis would be that 50% of the students are from wealthy homes, while the alternative hypothesis would be that 50% of the students are not from wealthy homes.
A random sample of 100 students in the said college would be carried out via a survey, and the null hypothesis would be tested.
If 40 of those students are not from wealthy homes, then the 50% null hypothesis would be rejected, and the alternative hypothesis would be accepted.
Scientific Hypothesis
In the scientific hypothesis, the researcher’s expectation from the experiment is achieved following a scientific method outlined below:
- Create the question
- Carry out a background research
- Creating a hypothesis
- Design an experiment
- Collect data
- Analyze the results
- Reach a conclusion
- Share the results
In the scientific hypothesis, the statement is a prediction; then, it evolves into a question, answered via research. It is at the point the hypothesis states the desired expectation. The next step after this is to test the hypothesis.
For example, the effect of Vitamin C supplements for a patient with cold symptoms is that the medication would help alleviate the effects of the cold.
As we established, a hypothesis predicts a relationship between variables that is yet to be proven. Creating a viable research hypothesis involves conducting research and broadening your knowledge about the subject via studying in other to choose the area of focus. Different types of hypotheses can be adopted to validate your predictions. The hypothesis should be testable in other to validate the claims.

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How to Develop a Good Research Hypothesis

The story of a research study begins by asking a question. Researchers all around the globe are asking curious questions and formulating research hypothesis. However, whether the research study provides an effective conclusion depends on how well one develops a good research hypothesis. Research hypothesis examples could help researchers get an idea as to how to write a good research hypothesis.
This blog will help you understand what is a research hypothesis, its characteristics and, how to formulate a research hypothesis
Table of Contents
What is Hypothesis?
Hypothesis is an assumption or an idea proposed for the sake of argument so that it can be tested. It is a precise, testable statement of what the researchers predict will be outcome of the study. Hypothesis usually involves proposing a relationship between two variables: the independent variable (what the researchers change) and the dependent variable (what the research measures).
What is a Research Hypothesis?
Research hypothesis is a statement that introduces a research question and proposes an expected result. It is an integral part of the scientific method that forms the basis of scientific experiments. Therefore, you need to be careful and thorough when building your research hypothesis. A minor flaw in the construction of your hypothesis could have an adverse effect on your experiment. In research, there is a convention that the hypothesis is written in two forms, the null hypothesis, and the alternative hypothesis (called the experimental hypothesis when the method of investigation is an experiment).

Essential Characteristics of a Good Research Hypothesis
As the hypothesis is specific, there is a testable prediction about what you expect to happen in a study. You may consider drawing hypothesis from previously published research based on the theory.
A good research hypothesis involves more effort than just a guess. In particular, your hypothesis may begin with a question that could be further explored through background research.
To help you formulate a promising research hypothesis, you should ask yourself the following questions:
- Is the language clear and focused?
- What is the relationship between your hypothesis and your research topic?
- Is your hypothesis testable? If yes, then how?
- What are the possible explanations that you might want to explore?
- Does your hypothesis include both an independent and dependent variable?
- Can you manipulate your variables without hampering the ethical standards?
- Does your research predict the relationship and outcome?
- Is your research simple and concise (avoids wordiness)?
- Is it clear with no ambiguity or assumptions about the readers’ knowledge
- Is your research observable and testable results?
- Is it relevant and specific to the research question or problem?

The questions listed above can be used as a checklist to make sure your hypothesis is based on a solid foundation. Furthermore, it can help you identify weaknesses in your hypothesis and revise it if necessary.
Source: Educational Hub
How to formulate an effective research hypothesis.
A testable hypothesis is not a simple statement. It is rather an intricate statement that needs to offer a clear introduction to a scientific experiment, its intentions, and the possible outcomes. However, there are some important things to consider when building a compelling hypothesis.
1. State the problem that you are trying to solve.
Make sure that the hypothesis clearly defines the topic and the focus of the experiment.
2. Try to write the hypothesis as an if-then statement.
Follow this template: If a specific action is taken, then a certain outcome is expected.
3. Define the variables
Independent variables are the ones that are manipulated, controlled, or changed. Independent variables are isolated from other factors of the study.
Dependent variables , as the name suggests are dependent on other factors of the study. They are influenced by the change in independent variable.
4. Scrutinize the hypothesis
The types of research hypothesis are stated below:
1. Simple Hypothesis
It predicts the relationship between a single dependent variable and a single independent variable.
2. Complex Hypothesis
It predicts the relationship between two or more independent and dependent variables.
3. Directional Hypothesis
It specifies the expected direction to be followed to determine the relationship between variables and is derived from theory. Furthermore, it implies the researcher’s intellectual commitment to a particular outcome.
4. Non-directional Hypothesis
It does not predict the exact direction or nature of the relationship between the two variables. The non-directional hypothesis is used when there is no theory involved or when findings contradict previous research.
5. Associative and Causal Hypothesis
The associative hypothesis defines interdependency between variables. A change in one variable results in the change of the other variable. On the other hand, the causal hypothesis proposes an effect on the dependent due to manipulation of the independent variable.
6. Null Hypothesis
Null hypothesis states a negative statement to support the researcher’s findings that there is no relationship between two variables. There will be no changes in the dependent variable due the manipulation of the independent variable. Furthermore, it states results are due to chance and are not significant in terms of supporting the idea being investigated.
7. Alternative Hypothesis
It states that there is a relationship between the two variables of the study and that the results are significant to the research topic. An experimental hypothesis predicts what changes will take place in the dependent variable when the independent variable is manipulated. Also, it states that the results are not due to chance and that they are significant in terms of supporting the theory being investigated.
Research Hypothesis Examples of Independent and Dependent Variables:
Research Hypothesis Example 1 The greater number of coal plants in a region (independent variable) increases water pollution (dependent variable). If you change the independent variable (building more coal factories), it will change the dependent variable (amount of water pollution).
Research Hypothesis Example 2 What is the effect of diet or regular soda (independent variable) on blood sugar levels (dependent variable)? If you change the independent variable (the type of soda you consume), it will change the dependent variable (blood sugar levels)
You should not ignore the importance of the above steps. The validity of your experiment and its results rely on a robust testable hypothesis. Developing a strong testable hypothesis has few advantages, it compels us to think intensely and specifically about the outcomes of a study. Consequently, it enables us to understand the implication of the question and the different variables involved in the study. Furthermore, it helps us to make precise predictions based on prior research. Hence, forming a hypothesis would be of great value to the research. Here are some good examples of testable hypotheses.
More importantly, you need to build a robust testable research hypothesis for your scientific experiments. A testable hypothesis is a hypothesis that can be proved or disproved as a result of experimentation.
Importance of a Testable Hypothesis
To devise and perform an experiment using scientific method, you need to make sure that your hypothesis is testable. To be considered testable, some essential criteria must be met:
- There must be a possibility to prove that the hypothesis is true.
- There must be a possibility to prove that the hypothesis is false.
- The results of the hypothesis must be reproducible.
Without these criteria, the hypothesis and the results will be vague. As a result, the experiment will not prove or disprove anything significant.
What are your experiences with building hypotheses for scientific experiments? What challenges did you face? How did you overcome these challenges? Please share your thoughts with us in the comments section.

Wow! You really simplified your explanation that even dummies would find it easy to comprehend. Thank you so much.
Thanks a lot for your valuable guidance.
I enjoy reading the post. Hypotheses are actually an intrinsic part in a study. It bridges the research question and the methodology of the study.
Useful piece!
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It very interesting to read the topic, can you guide me any specific example of hypothesis process establish throw the Demand and supply of the specific product in market
Nicely explained
It is really a useful for me Kindly give some examples of hypothesis
It was a well explained content ,can you please give me an example with the null and alternative hypothesis illustrated
clear and concise. thanks.
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Null hypothesis and Alternative Hypothesis
A hypothesis is an approximate explanation that relates to the set of facts that can be tested by certain further investigations. There are basically two types, namely, null hypothesis and alternative hypothesis . A research generally starts with a problem. Next, these hypotheses provide the researcher with some specific restatements and clarifications of the research problem.
The criteria of the research problem in the form of null hypothesis and alternative hypothesis should be expressed as a relationship between two or more variables. The criteria is that the statements should be the one that expresses the relationship between the two or more measurable variables. The null hypothesis and alternative hypothesis should carry clear implications for testing and stating relations.

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The major differences between the null hypothesis and alternative hypothesis and the research problems are that the research problems are simple questions that cannot be tested. These two hypotheses can be tested, though.
The null hypothesis and alternative hypothesis are required to be fragmented properly before the data collection and interpretation phase in the research. Well fragmented hypotheses indicate that the researcher has adequate knowledge in that particular area and is thus able to take the investigation further because they can use a much more systematic system. It gives direction to the researcher on his/her collection and interpretation of data.
The null hypothesis and alternative hypothesis are useful only if they state the expected relationship between the variables or if they are consistent with the existing body of knowledge. They should be expressed as simply and concisely as possible. They are useful if they have explanatory power.
The purpose and importance of the null hypothesis and alternative hypothesis are that they provide an approximate description of the phenomena. The purpose is to provide the researcher or an investigator with a relational statement that is directly tested in a research study. The purpose is to provide the framework for reporting the inferences of the study. The purpose is to behave as a working instrument of the theory. The purpose is to prove whether or not the test is supported, which is separated from the investigator’s own values and decisions. They also provide direction to the research.
The null hypothesis is generally denoted as H0. It states the exact opposite of what an investigator or an experimenter predicts or expects. It basically defines the statement which states that there is no exact or actual relationship between the variables.
The alternative hypothesis is generally denoted as H1. It makes a statement that suggests or advises a potential result or an outcome that an investigator or the researcher may expect. It has been categorized into two categories: directional alternative hypothesis and non directional alternative hypothesis.
The directional hypothesis is a kind that explains the direction of the expected findings. Sometimes this type of alternative hypothesis is developed to examine the relationship among the variables rather than a comparison between the groups.
The non directional hypothesis is a kind that has no definite direction of the expected findings being specified.
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Hypothesis Examples: Different Types in Science and Research

- DESCRIPTION Woman in Bed Examples of Hypothesis
- SOURCE Karen Moskowitz / The Image Bank / Getty Images
- PERMISSION Used under Getty Images license
A hypothesis is a stepping stone to proving a theory. There are numerous types of hypotheses that can be employed when seeking to prove a theory. Additionally, there are many hypothesis examples that can help you form your own hypothesis.
What Is a Hypothesis?
Simply put, a hypothesis is an idea that can be tested based on the evidence available. A concept or statement must be tested to be proven credible. This serves as a starting point for further investigation to prove the hypothesis by applying the scientific method . However, there are multiple variables that can affect the results, and therefore the idea must be tested multiple times.
Parts of a Hypothesis: Independent and Dependent Variables
Before diving into hypothesis examples, take a moment to understand independent and dependent variables .
an independent variable stands on its own and is not changed by other variables
the dependent variable depends on other factors
The independent variable can cause a change in the dependent variable, but the dependent variable cannot cause a change in the independent variable. For example:
How does the amount of makeup one applies affect how clear their skin is?
Here, the independent variable is the makeup, and the dependent variable is the skin. The variables are important because they help determine the cause and effect. In this example, the hypothesis could be:
The amount of makeup one wears correlates to how clear their skin is.
Therefore, this hypothesis must be tested before it can be proven correct.
Types of Hypotheses
The most common forms of hypotheses are:
Simple Hypothesis
Complex Hypothesis
Null Hypothesis
Alternative Hypothesis
Logical Hypothesis
Empirical Hypothesis
Statistical Hypothesis
See how these types of hypotheses are created through examples.
Simple Hypothesis Examples
A simple hypothesis predicts the relationship between two variables: the independent variable and the dependent variable. This relationship is demonstrated through these examples.
Drinking sugary drinks daily leads to being overweight.
Smoking cigarettes daily leads to lung cancer.
Getting at least 8 hours of sleep can make people more alert.
Complex Hypothesis Examples
A complex hypothesis describes a relationship between variables . However, it’s a relationship between two or more independent variables and two or more dependent variables. You can follow these examples to get a better understanding of a complex hypothesis.
Adults who 1) drink sugary beverages on a daily basis and 2) have a family history of health issues are more likely to 1) become overweight and 2) develop diabetes or other health issues.
Individuals that 1) smoke cigarettes and 2) live in large cities are more likely than others to have 1) respiratory problems and 2) an increased risk of cancer.
Individuals who 1) get an average of eight or more hours of sleep and 2) have a balanced diet and schedule are more likely to 1) be alert during the day and 2) have more energy.
Null Hypothesis Examples
A null hypothesis, denoted by H 0 , proposes that two factors or groups are unrelated and that there is no difference between certain characteristics of a population or process. You must test the likelihood of the null hypothesis, in tandem with an alternative hypothesis, in order to disprove or discredit it. Some examples of a null hypothesis include:
There is no significant change in a person’s health during the times when they drink green tea only or root beer only.
There is no significant change in an individual’s work habits whether they get eight hours or nine hours of sleep.
There is no significant change in the growth of a plant if one uses distilled water only or vitamin-rich water only to water it.
Alternative Hypothesis Examples
An alternative hypothesis, denoted by H 1 or H A , is a claim that is contradictory to the null hypothesis. Researchers will pair the alternative hypothesis with the null hypothesis in order to prove that there is no relation. If the null hypothesis is disproven, then the alternative hypothesis will be accepted. If the null hypothesis is not rejected, then the alternative hypothesis will not be accepted. Some examples of alternative hypotheses are:
A person’s health improves during the times when they drink green tea only, as opposed to root beer only.
Work habits improve during the times when one gets 8 hours of sleep only, as opposed to 9 hours of sleep only.
The growth of the plant improved during the times when it received vitamin-rich water only, as opposed to distilled water only.
Logical Hypothesis Examples
A logical hypothesis is a proposed explanation using limited evidence. Generally, you want to turn a logical hypothesis into an empirical hypothesis, putting your theories or postulations to the test. In reference to these examples, there is currently no evidence to support these hypotheses. However, you can form a hypothesis based on the data available to draw a logical conclusion.
Cacti experience more successful growth rates than tulips on Mars.
Beings from Mars would not be able to breathe the air in Earth's atmosphere.
Creatures found at the bottom of the ocean use anaerobic respiration rather than aerobic respiration.
Empirical Hypothesis Examples
An empirical hypothesis, or working hypothesis, comes to life when a theory is being put to the test using observation and experiment. It's no longer just an idea or notion. Rather, it is going through trial and error and perhaps changing around those independent variables.
Roses watered with liquid Vitamin B grow faster than roses watered with liquid Vitamin E.
Women taking vitamin E grow hair faster than those taking vitamin K.
Thirsty rats find their way through a maze quicker if there is water at the end of the maze.
In these examples, trial and error is leading to a series of findings. The results of these experiments can all be observed and proven over time.
Statistical Hypothesis Examples
A statistical hypothesis is an examination of a portion of a population or statistical model. In this type of analysis, you use statistical information from an area. For example, if you wanted to conduct a study on the life expectancy of people from Savannah, you would want to examine every single resident of Savannah. This is not practical. Therefore, you would conduct your research using a statistical hypothesis or a sample of Savannah's population.
50% of Savannah's population lives beyond the age of 70.
80% of the U.S. population gets a divorce because of irreconcilable differences.
45% of the poor in the U.S. are illiterate.
Parameters of a Good Hypothesis
For a hypothesis to be sound , hold tight to these tips.
Step 1: Ask Yourself Questions
Define the independent and dependent variables very specifically, and don't take on more than you can handle. Keep yourself laser-focused on one specific cause-and-effect theory.
Step 2: Be Logical and Use Precise Language
Keep your language clean and simple. State your hypothesis as concisely and to the point as possible. A hypothesis is usually written in a form where it proposes that, if something is done, then something else will occur. Usually, you’ll want to form your hypothesis as a statement, not a question. For example:
If I raise the temperature of a cup of water, then the amount of sugar that can be dissolved in it will be increased.
Step 3: Make Sure Your Hypothesis Is Testable
Any hypothesis will need proof. Your audience will have to see evidence and reason to believe your statement. For example, I may want to drink root beer all day, not green tea. If you're going to make me change my ways, I need some sound reasoning and experimental proof — perhaps case studies of others who lost weight, cleared up their skin and had a marked improvement in their immunity by drinking green tea.
Applying Your Hypothesis
Hypotheses and research are the backbone of science. A hypothesis that is well-stated, founded in truth, and that can withstand extensive and repeated research and experimentation can lead to new discoveries and breakthroughs.
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What is a research hypothesis: How to write it, types, and examples

Any research begins with a research question and a research hypothesis . A research question alone may not suffice to design the experiment(s) needed to answer it. A hypothesis is central to the scientific method. But what is a hypothesis ? A hypothesis is a testable statement that proposes a possible explanation to a phenomenon, and it may include a prediction. Next, you may ask what is a research hypothesis ? Simply put, a research hypothesis is a prediction or educated guess about the relationship between the variables that you want to investigate.
It is important to be thorough when developing your research hypothesis. Shortcomings in the framing of a hypothesis can affect the study design and the results. A better understanding of the research hypothesis definition and characteristics of a good hypothesis will make it easier for you to develop your own hypothesis for your research. Let’s dive in to know more about the types of research hypothesis , how to write a research hypothesis , and some research hypothesis examples .
What is a hypothesis ?
A hypothesis is based on the existing body of knowledge in a study area. Framed before the data are collected, a hypothesis states the tentative relationship between independent and dependent variables, along with a prediction of the outcome.
What is a research hypothesis ?
Young researchers starting out their journey are usually brimming with questions like “ What is a hypothesis ?” “ What is a research hypothesis ?” “How can I write a good research hypothesis ?”
A research hypothesis is a statement that proposes a possible explanation for an observable phenomenon or pattern. It guides the direction of a study and predicts the outcome of the investigation. A research hypothesis is testable, i.e., it can be supported or disproven through experimentation or observation.

Characteristics of a good hypothesis
Here are the characteristics of a good hypothesis :
- Clearly formulated and free of language errors and ambiguity
- Concise and not unnecessarily verbose
- Has clearly defined variables
- Testable and stated in a way that allows for it to be disproven
- Can be tested using a research design that is feasible, ethical, and practical
- Specific and relevant to the research problem
- Rooted in a thorough literature search
- Can generate new knowledge or understanding.
How to create an effective research hypothesis
A study begins with the formulation of a research question. A researcher then performs background research. This background information forms the basis for building a good research hypothesis . The researcher then performs experiments, collects, and analyzes the data, interprets the findings, and ultimately, determines if the findings support or negate the original hypothesis.
Let’s look at each step for creating an effective, testable, and good research hypothesis :
- Identify a research problem or question: Start by identifying a specific research problem.
- Review the literature: Conduct an in-depth review of the existing literature related to the research problem to grasp the current knowledge and gaps in the field.
- Formulate a clear and testable hypothesis : Based on the research question, use existing knowledge to form a clear and testable hypothesis . The hypothesis should state a predicted relationship between two or more variables that can be measured and manipulated. Improve the original draft till it is clear and meaningful.
- State the null hypothesis: The null hypothesis is a statement that there is no relationship between the variables you are studying.
- Define the population and sample: Clearly define the population you are studying and the sample you will be using for your research.
- Select appropriate methods for testing the hypothesis: Select appropriate research methods, such as experiments, surveys, or observational studies, which will allow you to test your research hypothesis .
Remember that creating a research hypothesis is an iterative process, i.e., you might have to revise it based on the data you collect. You may need to test and reject several hypotheses before answering the research problem.
How to write a research hypothesis
When you start writing a research hypothesis , you use an “if–then” statement format, which states the predicted relationship between two or more variables. Clearly identify the independent variables (the variables being changed) and the dependent variables (the variables being measured), as well as the population you are studying. Review and revise your hypothesis as needed.
An example of a research hypothesis in this format is as follows:
“ If [athletes] follow [cold water showers daily], then their [endurance] increases.”
Population: athletes
Independent variable: daily cold water showers
Dependent variable: endurance
You may have understood the characteristics of a good hypothesis . But note that a research hypothesis is not always confirmed; a researcher should be prepared to accept or reject the hypothesis based on the study findings.

Research hypothesis checklist
Following from above, here is a 10-point checklist for a good research hypothesis :
- Testable: A research hypothesis should be able to be tested via experimentation or observation.
- Specific: A research hypothesis should clearly state the relationship between the variables being studied.
- Based on prior research: A research hypothesis should be based on existing knowledge and previous research in the field.
- Falsifiable: A research hypothesis should be able to be disproven through testing.
- Clear and concise: A research hypothesis should be stated in a clear and concise manner.
- Logical: A research hypothesis should be logical and consistent with current understanding of the subject.
- Relevant: A research hypothesis should be relevant to the research question and objectives.
- Feasible: A research hypothesis should be feasible to test within the scope of the study.
- Reflects the population: A research hypothesis should consider the population or sample being studied.
- Uncomplicated: A good research hypothesis is written in a way that is easy for the target audience to understand.
By following this research hypothesis checklist , you will be able to create a research hypothesis that is strong, well-constructed, and more likely to yield meaningful results.

Types of research hypothesis
Different types of research hypothesis are used in scientific research:
1. Null hypothesis:
A null hypothesis states that there is no change in the dependent variable due to changes to the independent variable. This means that the results are due to chance and are not significant. A null hypothesis is denoted as H0 and is stated as the opposite of what the alternative hypothesis states.
Example: “ The newly identified virus is not zoonotic .”
2. Alternative hypothesis:
This states that there is a significant difference or relationship between the variables being studied. It is denoted as H1 or Ha and is usually accepted or rejected in favor of the null hypothesis.
Example: “ The newly identified virus is zoonotic .”
3. Directional hypothesis :
This specifies the direction of the relationship or difference between variables; therefore, it tends to use terms like increase, decrease, positive, negative, more, or less.
Example: “ The inclusion of intervention X decreases infant mortality compared to the original treatment .”
4. Non-directional hypothesis:
While it does not predict the exact direction or nature of the relationship between the two variables, a non-directional hypothesis states the existence of a relationship or difference between variables but not the direction, nature, or magnitude of the relationship. A non-directional hypothesis may be used when there is no underlying theory or when findings contradict previous research.
Example, “ Cats and dogs differ in the amount of affection they express .”
5. Simple hypothesis :
A simple hypothesis only predicts the relationship between one independent and another independent variable.
Example: “ Applying sunscreen every day slows skin aging .”
6 . Complex hypothesis :
A complex hypothesis states the relationship or difference between two or more independent and dependent variables.
Example: “ Applying sunscreen every day slows skin aging, reduces sun burn, and reduces the chances of skin cancer .” (Here, the three dependent variables are slowing skin aging, reducing sun burn, and reducing the chances of skin cancer.)
7. Associative hypothesis:
An associative hypothesis states that a change in one variable results in the change of the other variable. The associative hypothesis defines interdependency between variables.
Example: “ There is a positive association between physical activity levels and overall health .”
8 . Causal hypothesis:
A causal hypothesis proposes a cause-and-effect interaction between variables.
Example: “ Long-term alcohol use causes liver damage .”
Note that some of the types of research hypothesis mentioned above might overlap. The types of hypothesis chosen will depend on the research question and the objective of the study.

Research hypothesis examples
Here are some good research hypothesis examples :
“The use of a specific type of therapy will lead to a reduction in symptoms of depression in individuals with a history of major depressive disorder.”
“Providing educational interventions on healthy eating habits will result in weight loss in overweight individuals.”
“Plants that are exposed to certain types of music will grow taller than those that are not exposed to music.”
“The use of the plant growth regulator X will lead to an increase in the number of flowers produced by plants.”
Characteristics that make a research hypothesis weak are unclear variables, unoriginality, being too general or too vague, and being untestable. A weak hypothesis leads to weak research and improper methods.
Some bad research hypothesis examples (and the reasons why they are “bad”) are as follows:
“This study will show that treatment X is better than any other treatment . ” (This statement is not testable, too broad, and does not consider other treatments that may be effective.)
“This study will prove that this type of therapy is effective for all mental disorders . ” (This statement is too broad and not testable as mental disorders are complex and different disorders may respond differently to different types of therapy.)
“Plants can communicate with each other through telepathy . ” (This statement is not testable and lacks a scientific basis.)
Importance of testable hypothesis
If a research hypothesis is not testable, the results will not prove or disprove anything meaningful. The conclusions will be vague at best. A testable hypothesis helps a researcher focus on the study outcome and understand the implication of the question and the different variables involved. A testable hypothesis helps a researcher make precise predictions based on prior research.
To be considered testable, there must be a way to prove that the hypothesis is true or false; further, the results of the hypothesis must be reproducible.

Frequently asked questions on research hypothesis
1. what is the difference between research question and research hypothesis .
A research question defines the problem and helps outline the study objective(s). It is an open-ended statement that is exploratory or probing in nature. Therefore, it does not make predictions or assumptions. It helps a researcher identify what information to collect. A research hypothesis , however, is a specific, testable prediction about the relationship between variables. Accordingly, it guides the study design and data analysis approach.
2. When to reject null hypothesis ?
A null hypothesis should be rejected when the evidence from a statistical test shows that it is unlikely to be true. This happens when the test statistic (e.g., p -value) is less than the defined significance level (e.g., 0.05). Rejecting the null hypothesis does not necessarily mean that the alternative hypothesis is true; it simply means that the evidence found is not compatible with the null hypothesis.
3. How can I be sure my hypothesis is testable?
A testable hypothesis should be specific and measurable, and it should state a clear relationship between variables that can be tested with data. To ensure that your hypothesis is testable, consider the following:
- Clearly define the key variables in your hypothesis. You should be able to measure and manipulate these variables in a way that allows you to test the hypothesis.
- The hypothesis should predict a specific outcome or relationship between variables that can be measured or quantified.
- You should be able to collect the necessary data within the constraints of your study.
- It should be possible for other researchers to replicate your study, using the same methods and variables.
- Your hypothesis should be testable by using appropriate statistical analysis techniques, so you can draw conclusions, and make inferences about the population from the sample data.
- The hypothesis should be able to be disproven or rejected through the collection of data.
4. How do I revise my research hypothesis if my data does not support it?
If your data does not support your research hypothesis , you will need to revise it or develop a new one. You should examine your data carefully and identify any patterns or anomalies, re-examine your research question, and/or revisit your theory to look for any alternative explanations for your results. Based on your review of the data, literature, and theories, modify your research hypothesis to better align it with the results you obtained. Use your revised hypothesis to guide your research design and data collection. It is important to remain objective throughout the process.
5. I am performing exploratory research. Do I need to formulate a research hypothesis?
As opposed to “confirmatory” research, where a researcher has some idea about the relationship between the variables under investigation, exploratory research (or hypothesis-generating research) looks into a completely new topic about which limited information is available. Therefore, the researcher will not have any prior hypotheses. In such cases, a researcher will need to develop a post-hoc hypothesis. A post-hoc research hypothesis is generated after these results are known.
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Different Types of Hypotheses · 1. Null hypothesis · 2. Alternative hypothesis · 3. Simple hypothesis · 4. Complex hypothesis · 5. Associative and
Types of Hypothesis · Simple hypothesis · Complex hypothesis · Directional hypothesis · Non-directional hypothesis · Null hypothesis · Associative and casual
Types of Research Hypotheses · Simple Hypothesis: A simple hypothesis predicts the relationship between a single dependent variable and a single independent
In research, there is a convention that the hypothesis is written in two forms, the null hypothesis, and the alternative hypothesis (called
1. Simple Hypothesis · 2. Complex Hypothesis · 3. Directional Hypothesis · 4. Non-directional Hypothesis · 5. Associative and Causal Hypothesis · 6.
A minor flaw in the construction of your hypothesis could have an adverse effect on your experiment. In research, there is a convention that the hypothesis is
There are basically two types, namely, null hypothesis and alternative hypothesis. A research generally starts with a problem. Next, these hypotheses
Types of Hypotheses · Simple Hypothesis · Complex Hypothesis · Null Hypothesis · Alternative Hypothesis · Logical Hypothesis · Empirical Hypothesis · Statistical
TYPES OF HYPOTHESIS · Simple Hypothesis · Complex Hypothesis · Working or Research Hypothesis · Null Hypothesis · Alternative Hypothesis · Logical Hypothesis
A hypothesis is a testable statement that proposes a possible explanation to a phenomenon, and it may include a prediction. Next, you may ask