Definition of a Hypothesis

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A hypothesis is a prediction of what will be found at the outcome of a research project and is typically focused on the relationship between two different variables studied in the research. It is usually based on both theoretical expectations about how things work and already existing scientific evidence.

Within social science, a hypothesis can take two forms. It can predict that there is no relationship between two variables, in which case it is a null hypothesis . Or, it can predict the existence of a relationship between variables, which is known as an alternative hypothesis.

In either case, the variable that is thought to either affect or not affect the outcome is known as the independent variable, and the variable that is thought to either be affected or not is the dependent variable.

Researchers seek to determine whether or not their hypothesis, or hypotheses if they have more than one, will prove true. Sometimes they do, and sometimes they do not. Either way, the research is considered successful if one can conclude whether or not a hypothesis is true. 

Null Hypothesis

A researcher has a null hypothesis when she or he believes, based on theory and existing scientific evidence, that there will not be a relationship between two variables. For example, when examining what factors influence a person's highest level of education within the U.S., a researcher might expect that place of birth, number of siblings, and religion would not have an impact on the level of education. This would mean the researcher has stated three null hypotheses.

Alternative Hypothesis

Taking the same example, a researcher might expect that the economic class and educational attainment of one's parents, and the race of the person in question are likely to have an effect on one's educational attainment. Existing evidence and social theories that recognize the connections between wealth and cultural resources , and how race affects access to rights and resources in the U.S. , would suggest that both economic class and educational attainment of the one's parents would have a positive effect on educational attainment. In this case, economic class and educational attainment of one's parents are independent variables, and one's educational attainment is the dependent variable—it is hypothesized to be dependent on the other two.

Conversely, an informed researcher would expect that being a race other than white in the U.S. is likely to have a negative impact on a person's educational attainment. This would be characterized as a negative relationship, wherein being a person of color has a negative effect on one's educational attainment. In reality, this hypothesis proves true, with the exception of Asian Americans , who go to college at a higher rate than whites do. However, Blacks and Hispanics and Latinos are far less likely than whites and Asian Americans to go to college.

Formulating a Hypothesis

Formulating a hypothesis can take place at the very beginning of a research project , or after a bit of research has already been done. Sometimes a researcher knows right from the start which variables she is interested in studying, and she may already have a hunch about their relationships. Other times, a researcher may have an interest in ​a particular topic, trend, or phenomenon, but he may not know enough about it to identify variables or formulate a hypothesis.

Whenever a hypothesis is formulated, the most important thing is to be precise about what one's variables are, what the nature of the relationship between them might be, and how one can go about conducting a study of them.

Updated by Nicki Lisa Cole, Ph.D

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Home » What is a Hypothesis – Types, Examples and Writing Guide

What is a Hypothesis – Types, Examples and Writing Guide

Table of Contents

What is a Hypothesis

Definition:

Hypothesis is an educated guess or proposed explanation for a phenomenon, based on some initial observations or data. It is a tentative statement that can be tested and potentially proven or disproven through further investigation and experimentation.

Hypothesis is often used in scientific research to guide the design of experiments and the collection and analysis of data. It is an essential element of the scientific method, as it allows researchers to make predictions about the outcome of their experiments and to test those predictions to determine their accuracy.

Types of Hypothesis

Types of Hypothesis are as follows:

Research Hypothesis

A research hypothesis is a statement that predicts a relationship between variables. It is usually formulated as a specific statement that can be tested through research, and it is often used in scientific research to guide the design of experiments.

Null Hypothesis

The null hypothesis is a statement that assumes there is no significant difference or relationship between variables. It is often used as a starting point for testing the research hypothesis, and if the results of the study reject the null hypothesis, it suggests that there is a significant difference or relationship between variables.

Alternative Hypothesis

An alternative hypothesis is a statement that assumes there is a significant difference or relationship between variables. It is often used as an alternative to the null hypothesis and is tested against the null hypothesis to determine which statement is more accurate.

Directional Hypothesis

A directional hypothesis is a statement that predicts the direction of the relationship between variables. For example, a researcher might predict that increasing the amount of exercise will result in a decrease in body weight.

Non-directional Hypothesis

A non-directional hypothesis is a statement that predicts the relationship between variables but does not specify the direction. For example, a researcher might predict that there is a relationship between the amount of exercise and body weight, but they do not specify whether increasing or decreasing exercise will affect body weight.

Statistical Hypothesis

A statistical hypothesis is a statement that assumes a particular statistical model or distribution for the data. It is often used in statistical analysis to test the significance of a particular result.

Composite Hypothesis

A composite hypothesis is a statement that assumes more than one condition or outcome. It can be divided into several sub-hypotheses, each of which represents a different possible outcome.

Empirical Hypothesis

An empirical hypothesis is a statement that is based on observed phenomena or data. It is often used in scientific research to develop theories or models that explain the observed phenomena.

Simple Hypothesis

A simple hypothesis is a statement that assumes only one outcome or condition. It is often used in scientific research to test a single variable or factor.

Complex Hypothesis

A complex hypothesis is a statement that assumes multiple outcomes or conditions. It is often used in scientific research to test the effects of multiple variables or factors on a particular outcome.

Applications of Hypothesis

Hypotheses are used in various fields to guide research and make predictions about the outcomes of experiments or observations. Here are some examples of how hypotheses are applied in different fields:

  • Science : In scientific research, hypotheses are used to test the validity of theories and models that explain natural phenomena. For example, a hypothesis might be formulated to test the effects of a particular variable on a natural system, such as the effects of climate change on an ecosystem.
  • Medicine : In medical research, hypotheses are used to test the effectiveness of treatments and therapies for specific conditions. For example, a hypothesis might be formulated to test the effects of a new drug on a particular disease.
  • Psychology : In psychology, hypotheses are used to test theories and models of human behavior and cognition. For example, a hypothesis might be formulated to test the effects of a particular stimulus on the brain or behavior.
  • Sociology : In sociology, hypotheses are used to test theories and models of social phenomena, such as the effects of social structures or institutions on human behavior. For example, a hypothesis might be formulated to test the effects of income inequality on crime rates.
  • Business : In business research, hypotheses are used to test the validity of theories and models that explain business phenomena, such as consumer behavior or market trends. For example, a hypothesis might be formulated to test the effects of a new marketing campaign on consumer buying behavior.
  • Engineering : In engineering, hypotheses are used to test the effectiveness of new technologies or designs. For example, a hypothesis might be formulated to test the efficiency of a new solar panel design.

How to write a Hypothesis

Here are the steps to follow when writing a hypothesis:

Identify the Research Question

The first step is to identify the research question that you want to answer through your study. This question should be clear, specific, and focused. It should be something that can be investigated empirically and that has some relevance or significance in the field.

Conduct a Literature Review

Before writing your hypothesis, it’s essential to conduct a thorough literature review to understand what is already known about the topic. This will help you to identify the research gap and formulate a hypothesis that builds on existing knowledge.

Determine the Variables

The next step is to identify the variables involved in the research question. A variable is any characteristic or factor that can vary or change. There are two types of variables: independent and dependent. The independent variable is the one that is manipulated or changed by the researcher, while the dependent variable is the one that is measured or observed as a result of the independent variable.

Formulate the Hypothesis

Based on the research question and the variables involved, you can now formulate your hypothesis. A hypothesis should be a clear and concise statement that predicts the relationship between the variables. It should be testable through empirical research and based on existing theory or evidence.

Write the Null Hypothesis

The null hypothesis is the opposite of the alternative hypothesis, which is the hypothesis that you are testing. The null hypothesis states that there is no significant difference or relationship between the variables. It is important to write the null hypothesis because it allows you to compare your results with what would be expected by chance.

Refine the Hypothesis

After formulating the hypothesis, it’s important to refine it and make it more precise. This may involve clarifying the variables, specifying the direction of the relationship, or making the hypothesis more testable.

Examples of Hypothesis

Here are a few examples of hypotheses in different fields:

  • Psychology : “Increased exposure to violent video games leads to increased aggressive behavior in adolescents.”
  • Biology : “Higher levels of carbon dioxide in the atmosphere will lead to increased plant growth.”
  • Sociology : “Individuals who grow up in households with higher socioeconomic status will have higher levels of education and income as adults.”
  • Education : “Implementing a new teaching method will result in higher student achievement scores.”
  • Marketing : “Customers who receive a personalized email will be more likely to make a purchase than those who receive a generic email.”
  • Physics : “An increase in temperature will cause an increase in the volume of a gas, assuming all other variables remain constant.”
  • Medicine : “Consuming a diet high in saturated fats will increase the risk of developing heart disease.”

Purpose of Hypothesis

The purpose of a hypothesis is to provide a testable explanation for an observed phenomenon or a prediction of a future outcome based on existing knowledge or theories. A hypothesis is an essential part of the scientific method and helps to guide the research process by providing a clear focus for investigation. It enables scientists to design experiments or studies to gather evidence and data that can support or refute the proposed explanation or prediction.

The formulation of a hypothesis is based on existing knowledge, observations, and theories, and it should be specific, testable, and falsifiable. A specific hypothesis helps to define the research question, which is important in the research process as it guides the selection of an appropriate research design and methodology. Testability of the hypothesis means that it can be proven or disproven through empirical data collection and analysis. Falsifiability means that the hypothesis should be formulated in such a way that it can be proven wrong if it is incorrect.

In addition to guiding the research process, the testing of hypotheses can lead to new discoveries and advancements in scientific knowledge. When a hypothesis is supported by the data, it can be used to develop new theories or models to explain the observed phenomenon. When a hypothesis is not supported by the data, it can help to refine existing theories or prompt the development of new hypotheses to explain the phenomenon.

When to use Hypothesis

Here are some common situations in which hypotheses are used:

  • In scientific research , hypotheses are used to guide the design of experiments and to help researchers make predictions about the outcomes of those experiments.
  • In social science research , hypotheses are used to test theories about human behavior, social relationships, and other phenomena.
  • I n business , hypotheses can be used to guide decisions about marketing, product development, and other areas. For example, a hypothesis might be that a new product will sell well in a particular market, and this hypothesis can be tested through market research.

Characteristics of Hypothesis

Here are some common characteristics of a hypothesis:

  • Testable : A hypothesis must be able to be tested through observation or experimentation. This means that it must be possible to collect data that will either support or refute the hypothesis.
  • Falsifiable : A hypothesis must be able to be proven false if it is not supported by the data. If a hypothesis cannot be falsified, then it is not a scientific hypothesis.
  • Clear and concise : A hypothesis should be stated in a clear and concise manner so that it can be easily understood and tested.
  • Based on existing knowledge : A hypothesis should be based on existing knowledge and research in the field. It should not be based on personal beliefs or opinions.
  • Specific : A hypothesis should be specific in terms of the variables being tested and the predicted outcome. This will help to ensure that the research is focused and well-designed.
  • Tentative: A hypothesis is a tentative statement or assumption that requires further testing and evidence to be confirmed or refuted. It is not a final conclusion or assertion.
  • Relevant : A hypothesis should be relevant to the research question or problem being studied. It should address a gap in knowledge or provide a new perspective on the issue.

Advantages of Hypothesis

Hypotheses have several advantages in scientific research and experimentation:

  • Guides research: A hypothesis provides a clear and specific direction for research. It helps to focus the research question, select appropriate methods and variables, and interpret the results.
  • Predictive powe r: A hypothesis makes predictions about the outcome of research, which can be tested through experimentation. This allows researchers to evaluate the validity of the hypothesis and make new discoveries.
  • Facilitates communication: A hypothesis provides a common language and framework for scientists to communicate with one another about their research. This helps to facilitate the exchange of ideas and promotes collaboration.
  • Efficient use of resources: A hypothesis helps researchers to use their time, resources, and funding efficiently by directing them towards specific research questions and methods that are most likely to yield results.
  • Provides a basis for further research: A hypothesis that is supported by data provides a basis for further research and exploration. It can lead to new hypotheses, theories, and discoveries.
  • Increases objectivity: A hypothesis can help to increase objectivity in research by providing a clear and specific framework for testing and interpreting results. This can reduce bias and increase the reliability of research findings.

Limitations of Hypothesis

Some Limitations of the Hypothesis are as follows:

  • Limited to observable phenomena: Hypotheses are limited to observable phenomena and cannot account for unobservable or intangible factors. This means that some research questions may not be amenable to hypothesis testing.
  • May be inaccurate or incomplete: Hypotheses are based on existing knowledge and research, which may be incomplete or inaccurate. This can lead to flawed hypotheses and erroneous conclusions.
  • May be biased: Hypotheses may be biased by the researcher’s own beliefs, values, or assumptions. This can lead to selective interpretation of data and a lack of objectivity in research.
  • Cannot prove causation: A hypothesis can only show a correlation between variables, but it cannot prove causation. This requires further experimentation and analysis.
  • Limited to specific contexts: Hypotheses are limited to specific contexts and may not be generalizable to other situations or populations. This means that results may not be applicable in other contexts or may require further testing.
  • May be affected by chance : Hypotheses may be affected by chance or random variation, which can obscure or distort the true relationship between variables.

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The Craft of Writing a Strong Hypothesis

Deeptanshu D

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

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-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.

formulation of hypothesis meaning

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How to Write a Strong Hypothesis | Guide & Examples

Published on 6 May 2022 by Shona McCombes .

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations, and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more variables . An independent variable is something the researcher changes or controls. A dependent variable is something the researcher observes and measures.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

Prevent plagiarism, run a free check.

Step 1: ask a question.

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2: Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalise more complex constructs.

Step 3: Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

Step 4: Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

  • The relevant variables
  • The specific group being studied
  • The predicted outcome of the experiment or analysis

Step 5: Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in if … then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

Step 6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis. The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

A hypothesis is not just a guess. It should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations, and statistical analysis of data).

A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (‘ x affects y because …’).

A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses. In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.

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How to Develop a Good Research Hypothesis

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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).

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?

research hypothesis example

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 a 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

Evaluate assumptions, predictions, and evidence rigorously to refine your understanding.

Types of Research 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.

Frequently Asked Questions

The steps to write a research hypothesis are: 1. Stating the problem: Ensure that the hypothesis defines the research problem 2. Writing a hypothesis as an 'if-then' statement: Include the action and the expected outcome of your study by following a ‘if-then’ structure. 3. Defining the variables: Define the variables as Dependent or Independent based on their dependency to other factors. 4. Scrutinizing the hypothesis: Identify the type of your hypothesis

Hypothesis testing is a statistical tool which is used to make inferences about a population data to draw conclusions for a particular hypothesis.

Hypothesis in statistics is a formal statement about the nature of a population within a structured framework of a statistical model. It is used to test an existing hypothesis by studying a population.

Research hypothesis is a statement that introduces a research question and proposes an expected result. It forms the basis of scientific experiments.

The different types of hypothesis in research are: • Null hypothesis: Null hypothesis is a negative statement to support the researcher’s findings that there is no relationship between two variables. • Alternate hypothesis: Alternate hypothesis predicts the relationship between the two variables of the study. • Directional hypothesis: Directional hypothesis specifies the expected direction to be followed to determine the relationship between variables. • Non-directional hypothesis: Non-directional hypothesis does not predict the exact direction or nature of the relationship between the two variables. • Simple hypothesis: Simple hypothesis predicts the relationship between a single dependent variable and a single independent variable. • Complex hypothesis: Complex hypothesis predicts the relationship between two or more independent and dependent variables. • Associative and casual hypothesis: Associative and casual hypothesis predicts the relationship between two or more independent and dependent variables. • Empirical hypothesis: Empirical hypothesis can be tested via experiments and observation. • Statistical hypothesis: A statistical hypothesis utilizes statistical models to draw conclusions about broader populations.

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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.

So Good so Amazing

Good to learn

Thanks a lot for explaining to my level of understanding

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What Is A Research (Scientific) Hypothesis? A plain-language explainer + examples

By:  Derek Jansen (MBA)  | Reviewed By: Dr Eunice Rautenbach | June 2020

If you’re new to the world of research, or it’s your first time writing a dissertation or thesis, you’re probably noticing that the words “research hypothesis” and “scientific hypothesis” are used quite a bit, and you’re wondering what they mean in a research context .

“Hypothesis” is one of those words that people use loosely, thinking they understand what it means. However, it has a very specific meaning within academic research. So, it’s important to understand the exact meaning before you start hypothesizing. 

Research Hypothesis 101

  • What is a hypothesis ?
  • What is a research hypothesis (scientific hypothesis)?
  • Requirements for a research hypothesis
  • Definition of a research hypothesis
  • The null hypothesis

What is a hypothesis?

Let’s start with the general definition of a hypothesis (not a research hypothesis or scientific hypothesis), according to the Cambridge Dictionary:

Hypothesis: an idea or explanation for something that is based on known facts but has not yet been proved.

In other words, it’s a statement that provides an explanation for why or how something works, based on facts (or some reasonable assumptions), but that has not yet been specifically tested . For example, a hypothesis might look something like this:

Hypothesis: sleep impacts academic performance.

This statement predicts that academic performance will be influenced by the amount and/or quality of sleep a student engages in – sounds reasonable, right? It’s based on reasonable assumptions , underpinned by what we currently know about sleep and health (from the existing literature). So, loosely speaking, we could call it a hypothesis, at least by the dictionary definition.

But that’s not good enough…

Unfortunately, that’s not quite sophisticated enough to describe a research hypothesis (also sometimes called a scientific hypothesis), and it wouldn’t be acceptable in a dissertation, thesis or research paper . In the world of academic research, a statement needs a few more criteria to constitute a true research hypothesis . 

What is a research hypothesis?

A research hypothesis (also called a scientific hypothesis) is a statement about the expected outcome of a study (for example, a dissertation or thesis). To constitute a quality hypothesis, the statement needs to have three attributes – specificity , clarity and testability .

Let’s take a look at these more closely.

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formulation of hypothesis meaning

Hypothesis Essential #1: Specificity & Clarity

A good research hypothesis needs to be extremely clear and articulate about both what’ s being assessed (who or what variables are involved ) and the expected outcome (for example, a difference between groups, a relationship between variables, etc.).

Let’s stick with our sleepy students example and look at how this statement could be more specific and clear.

Hypothesis: Students who sleep at least 8 hours per night will, on average, achieve higher grades in standardised tests than students who sleep less than 8 hours a night.

As you can see, the statement is very specific as it identifies the variables involved (sleep hours and test grades), the parties involved (two groups of students), as well as the predicted relationship type (a positive relationship). There’s no ambiguity or uncertainty about who or what is involved in the statement, and the expected outcome is clear.

Contrast that to the original hypothesis we looked at – “Sleep impacts academic performance” – and you can see the difference. “Sleep” and “academic performance” are both comparatively vague , and there’s no indication of what the expected relationship direction is (more sleep or less sleep). As you can see, specificity and clarity are key.

A good research hypothesis needs to be very clear about what’s being assessed and very specific about the expected outcome.

Hypothesis Essential #2: Testability (Provability)

A statement must be testable to qualify as a research hypothesis. In other words, there needs to be a way to prove (or disprove) the statement. If it’s not testable, it’s not a hypothesis – simple as that.

For example, consider the hypothesis we mentioned earlier:

Hypothesis: Students who sleep at least 8 hours per night will, on average, achieve higher grades in standardised tests than students who sleep less than 8 hours a night.  

We could test this statement by undertaking a quantitative study involving two groups of students, one that gets 8 or more hours of sleep per night for a fixed period, and one that gets less. We could then compare the standardised test results for both groups to see if there’s a statistically significant difference. 

Again, if you compare this to the original hypothesis we looked at – “Sleep impacts academic performance” – you can see that it would be quite difficult to test that statement, primarily because it isn’t specific enough. How much sleep? By who? What type of academic performance?

So, remember the mantra – if you can’t test it, it’s not a hypothesis 🙂

A good research hypothesis must be testable. In other words, you must able to collect observable data in a scientifically rigorous fashion to test it.

Defining A Research Hypothesis

You’re still with us? Great! Let’s recap and pin down a clear definition of a hypothesis.

A research hypothesis (or scientific hypothesis) is a statement about an expected relationship between variables, or explanation of an occurrence, that is clear, specific and testable.

So, when you write up hypotheses for your dissertation or thesis, make sure that they meet all these criteria. If you do, you’ll not only have rock-solid hypotheses but you’ll also ensure a clear focus for your entire research project.

What about the null hypothesis?

You may have also heard the terms null hypothesis , alternative hypothesis, or H-zero thrown around. At a simple level, the null hypothesis is the counter-proposal to the original hypothesis.

For example, if the hypothesis predicts that there is a relationship between two variables (for example, sleep and academic performance), the null hypothesis would predict that there is no relationship between those variables.

At a more technical level, the null hypothesis proposes that no statistical significance exists in a set of given observations and that any differences are due to chance alone.

And there you have it – hypotheses in a nutshell. 

If you have any questions, be sure to leave a comment below and we’ll do our best to help you. If you need hands-on help developing and testing your hypotheses, consider our private coaching service , where we hold your hand through the research journey.

formulation of hypothesis meaning

Psst… there’s more (for free)

This post is part of our dissertation mini-course, which covers everything you need to get started with your dissertation, thesis or research project. 

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12 Comments

Lynnet Chikwaikwai

Very useful information. I benefit more from getting more information in this regard.

Dr. WuodArek

Very great insight,educative and informative. Please give meet deep critics on many research data of public international Law like human rights, environment, natural resources, law of the sea etc

Afshin

In a book I read a distinction is made between null, research, and alternative hypothesis. As far as I understand, alternative and research hypotheses are the same. Can you please elaborate? Best Afshin

GANDI Benjamin

This is a self explanatory, easy going site. I will recommend this to my friends and colleagues.

Lucile Dossou-Yovo

Very good definition. How can I cite your definition in my thesis? Thank you. Is nul hypothesis compulsory in a research?

Egya Salihu

Please what is the difference between alternate hypothesis and research hypothesis?

Mulugeta Tefera

It is a very good explanation. However, it limits hypotheses to statistically tasteable ideas. What about for qualitative researches or other researches that involve quantitative data that don’t need statistical tests?

Derek Jansen

In qualitative research, one typically uses propositions, not hypotheses.

Samia

could you please elaborate it more

Patricia Nyawir

I’ve benefited greatly from these notes, thank you.

Hopeson Khondiwa

This is very helpful

Dr. Andarge

well articulated ideas are presented here, thank you for being reliable sources of information

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What is Hypothesis?

  • Post last modified: 20 April 2021
  • Reading time: 20 mins read
  • Post category: Research Methodology

Hypothesis is a proposition which can be put to a test to determine validity and is useful for further research.

Hypothesis is a statement which can be proved or disproved. It is a statement capable of being tested. In a sense, hypothesis is a question which definitely has an answer. Hypothesis aids us a great deal while collecting, tabulating and analyzing data and other relevant information.

Table of Content

  • 1 What is Hypothesis?
  • 2 Hypothesis Definition
  • 3 Meaning of Hypothesis
  • 4.1 Conceptual Clarity
  • 4.2 Need of the empirical referents
  • 4.3 Hypothesis should be specific
  • 4.4 Hypothesis should be within the ambit of the available research techniques
  • 4.5 Hypothesis should be consistent with the theory
  • 4.6 Hypothesis should be concerned with observable facts and empirical events
  • 4.7 Hypothesis should be simple
  • 5 Formulation of Hypothesis
  • 6 Null Hypothesis
  • 7.1 Stating the hypothesis of interest
  • 7.2 Collection of relevant data and information
  • 7.3 Formation of null hypothesis
  • 7.4 Alternative Hypothesis
  • 7.5 Selection of suitable test statistic
  • 7.6 Determine the level of significance
  • 7.7 Decision

Hypothesis thus is inevitable in any kind of research, if it is to be carried out successfully. The meaning and exact nature of hypothesis will become clear from the following definitions.

Hypothesis Definition

Meaning of hypothesis.

From the above mentioned definitions of hypothesis, its meaning can be explained in the following ways:

  • At the primary level, a hypothesis is the possible and probable explanation of the sequence of happenings or data.
  • Sometimes, hypothesis may emerge from an imagination, common sense or a sudden event.
  • Hypothesis can be a probable answer to the research problem undertaken for study.
  • Hypothesis may not always be true. It can get disproven. In other words, hypothesis need not always be a true proposition.
  • Hypothesis, in a sense, is an attempt to present the interrelations that exist in the available data or information.
  • Hypothesis is not an individual opinion or community thought. Instead, it is a philosophical means which is to be used for research purpose. Hypothesis is not to be considered as the ultimate objective; rather it is to be taken as the means of explaining scientifically the prevailing situation.

Characteristics of Hypothesis

Not all the hypotheses are good and useful from the point of view of research. It is only the few hypotheses satisfying certain criteria that are good, useful and directive in the research work undertaken.

The characteristics of a good hypothesis can be listed as below.

Conceptual Clarity

Need of the empirical referents, hypothesis should be specific, hypothesis should be within the ambit of the available research techniques, hypothesis should be consistent with the theory, hypothesis should be concerned with observable facts and empirical events, hypothesis should be simple.

The concepts used while framing hypothesis should be crystal clear and unambiguous. Such concepts must be clearly defined so that they become lucid and acceptable to everyone.

How are the newly developed concepts interrelated and how are they linked with the old one is to be very clear so that the hypothesis framed on their basis also carries the same clarity. A hypothesis embodying unclear and ambiguous concepts can to a great extent undermine the successful completion of the research work.

A hypothesis can be useful in the research work undertaken only when it has links with some empirical referents. Hypothesis based on moral values and ideals are useless as they cannot be tested. Similarly, hypothesis containing opinions as good and bad or expectation with respect to something are not testable and therefore useless.

For example, ‘current account deficit can be lowered if people change their attitude towards gold’ is a hypothesis encompassing expectation. In case of such a hypothesis, the attitude towards gold is something which cannot clearly be described and therefore a hypothesis which embodies such an unclear thing cannot be tested and proved or disproved. In short, the hypothesis should be linked with some testable referents.

For the successful conduction of research, it is necessary that the hypothesis is specific and presented in a precise manner. Hypothesis which is general, too ambitious and grandiose in scope is not to be made as such hypothesis cannot be easily put to test. A hypothesis is to be based on such concepts which are precise and empirical in nature. A hypothesis should give a clear idea about the indicators which are to be used.

For example, a hypothesis that economic power is increasingly getting concentrated in few hands in India should enable us to define the concept of economic power. It should be explicated in terms of the measurable indicator like income, wealth, etc. Such specificity in the formulation of hypothesis ensures that the research is practicable and significant.

While framing the hypothesis, the researcher should be aware of the available research techniques and should see that the hypothesis framed is testable on the basis of them.

In other words, a hypothesis should be researchable and for this, it is important that a due thought has been given to the methods and techniques which can be used to measure the concepts and variables embodied in the hypothesis.

It does not, however, mean that hypotheses which are not testable with the available techniques of research are not to be made. If the problem is too significant and therefore the hypothesis framed becomes too ambitious and complex, it’s testing becomes possible with the development of new research techniques or the hypothesis itself leads to the development of new research techniques.

A hypothesis must be related to the existing theory or should have a theoretical orientation. The growth of the knowledge takes place in the sequence of facts, hypothesis, theory and law or principles.

It means the hypothesis should have a correspondence with the existing facts and theory. If the hypothesis is related to some theory, the research work will enable us to support, modify or refute the existing theory. Theoretical orientation of the hypothesis ensures that it becomes scientifically useful.

According to Prof. Goode and Prof. Hatt, research work can contribute to the existing knowledge only when the hypothesis is related to some theory.

This enables us to explain the observed facts and situations and also verify the framed hypothesis.

In the words of Prof. Cohen and Prof. Nagel, “hypothesis must be formulated in such a manner that deduction can be made from it and that consequently a decision can be reached as to whether it does or does not explain the facts considered.

If the research work based on a hypothesis is to be successful, it is necessary that the later is as simple and easy as possible. An ambition of finding out something new may lead the researcher to frame an unrealistic and unclear hypothesis. Such a temptation is to be avoided.

Framing a simple, easy and testable hypothesis requires that the researcher is well acquainted with the related concepts.

Formulation of Hypothesis

The real beginning of any research is made with the formulation of hypothesis. In a sense, research is nothing but accepting the hypothesis by proving it or rejecting it if it is disproved or modifying it.

Moreover, in any type of research work, the information and data is to be collected with reference to the hypothesis and the concepts embodied in it. Hypothesis therefore occupies an important place in any type of research.

Formulation of hypothesis, however, requires that the difficulties encountered are overcome. A researcher may suffer from a number of difficulties at the stage of formulating a good hypothesis

  • The researcher should have a thorough knowledge of the accepted theories and basic concepts of that research area where he has decided to work in.
  • The researcher should also acquire the logical and scientific thinking power to frame a hypothesis based on the theories and basic concepts known to him.
  • The researcher should also be well acquainted with the available research methods and techniques.

Normally, the hypothesis made in the beginning of research is of crude or working nature. Such a working hypothesis is to be made while planning a research work. As the research work proceeds with the working hypothesis, new information, data and evidence becomes available. In the light of new information and evidence, the working hypothesis is to be modified and revised.

Sometimes, the working hypothesis changes in a significant way after the modifications are made. In some researches, the hypothesis is formulated not in the beginning but at the time of classification and analysis of data and information.

In the case of such a hypothesis also it becomes necessary that new or additional information is collected. It thus implies that every hypothesis is subject to change. In order to put the research work in an operative mode, several alternative hypotheses are made in the beginning.

While framing such hypotheses utmost care is to be taken while using the concepts. The nature of the hypothesis should be such that it enables the researcher to find out something new, something which is previously unknown.

In the context of research work and while performing the hypothesis testing exercise, both the alternative hypothesis which is to be proved and accepted and null hypothesis, which is to be disproved, are important and required.

The main hypothesis of the research work is the research hypothesis or the alternative hypothesis. Researcher’s job is to collect information and data so as to prove the alternative hypothesis so that it can be accepted. Null hypothesis on the other hand is the exact opposite of research or alternative hypothesis.

Null hypothesis is also called a hypothesis with no difference. Like the research or alternative hypothesis, the null hypothesis is also a statement.

The logic behind formulating a null hypothesis is that it is always easy to prove that a statement is wrong than to prove that a statement (research hypothesis) is cent percent true.

In short, while framing hypothesis for research work, it is important that at least two hypotheses are framed, one of which is a null hypothesis and the other one is an alternative hypothesis.

For instance, a null hypothesis and alternative hypothesis can be as below.

Null Hypothesis

The average age of entry in to the labour market of commerce graduates is 22 years.

However, the collected data and information, when analysed, reveals that Hypothesis the average entry age is greater than or less than 22 years, then the null hypothesis gets rejected.

In such a case the alternative hypothesis can be as under

  • The average age of entry into the labour market is greater than 22 years (> 22)
  • The average age of entry into the labour market is less than 22 years (< 22)
  • The average age of entry into the labour market is not 22 years (‘“ 22)

Test of Hypothesis

As stated in the beginning, the hypothesis formulation marks the beginning of any research. After the hypothesis is formulated in the context of a research problem, next process involves a collection of relevant data and information and analysis of the same using an appropriate statistical technique, which proves or disproves the hypothesis formulated in the beginning.

The testing of hypothesis thus represents the end of the research work. Testing of hypothesis can be considered as the most important step in any type of research work as it determines the fruitfulness of the research work.

Unless the hypothesis is tested, it will only remain an inference or a proposition. The act of determining the validity of the hypothesis based on the collected data is called the testing of hypothesis.

The exercise of hypothesis testing is a systematic work and normally involves following stages or steps:

Stating the hypothesis of interest

Collection of relevant data and information, formation of null hypothesis, alternative hypothesis, selection of suitable test statistic, determine the level of significance.

Based on the research problem and a primitive understanding of the relationship between the variables involved, a researcher formulates a hypothesis of interest or a research hypothesis which he wants to prove.

Given the research problem and the formulated hypothesis of interest, the next step is to collect the relevant data and information to proceed further towards the end objective (i.e. proving the research hypothesis).

For the testing purpose, a null hypothesis is formed based on the statistical data. The null hypothesis is also called as the hypothesis with no difference.

In other words, null hypothesis states that there is no difference between the variables involved in the hypothesis or the variables are not related.

For example, if the research hypothesis is that the commerce graduates are more employable than the arts graduates, then the null hypothesis will be that both are equally employable or that there is no difference in the employment opportunities available to both.

If in research hypothesis, price and demand are said to be inversely related, the null hypothesis assumes them independent or states that price and demand are not related.

After the formulation of null hypothesis, alternative hypothesis can be derived. Alternative hypothesis is the negation of null hypothesis and can be more than one and conform to the research hypothesis.

In the example of employability, the alternative hypothesis can be

  • commerce graduates are more employable or arts graduates are more employable
  • commerce graduates are having more employability
  • arts graduates are having more employability.

The next step in the hypothesis testing exercise is that of selecting an appropriate statistical test. It can be chi-square test, t-test or f-test or any other test. Such a test is carried out at a given level of significance.

As stated in the above step a statistical test is conducted at a given level of significance

  • A level of significance indicates the probability of rejecting or accepting the null hypothesis.

The last step in testing hypothesis is that of taking a decision on the basis of the given level of significance

  • It is seen whether the null hypothesis falls in the accepting region or in rejecting region and accordingly a decision is taken. In this way, the acceptance or rejection of null hypothesis determines the acceptance or rejection of the initial research hypothesis.

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Investigation and Management of Disease in Wild Animals pp 73–86 Cite as

Formulating and Testing Hypotheses

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The term hypothesis has been mentioned several times in the preceding chapters. The definition that will be used here is that a hypothesis is a proposition set forth as explanation for the occurrence of a specified phenomenon. The basis of scientific investigation is the collection of information that is used either to formulate or to test hypotheses. One assesses the important variables and tries to build a model or hypothesis that explains the observed phenomenon. In general, a hypothesis is formulated by rephrasing the objective of a study as a statement, e.g., if the objective of an investigation is to determine if a pesticide is safe, the resulting hypothesis might be “ the pesticide is not safe ”, or alternatively that “ the pesticide is safe ”. A hypothesis is a statistical hypothesis only if it is stated in terms related to the distribution of populations. The general hypothesis above might be refined to: “ this pesticide, when used as directed, has no effect on the average number of robins in an area ”, which is a testable hypothesis. The hypothesis to be tested is called the null hypothesis (H 0 ). The alternative hypothesis (H 1 ) for the above example would be “ this pesticide, when used as directed, has an effect on the average number of robins in an area”. In testing a hypothesis, H 0 is considered to be true, unless the sample data indicate otherwise, (i.e., that the pesticide is innocent, unless proven guilty). Testing cannot prove H 0 to be true but the results can cause it to be rejected. In accepting or rejecting H 0 , two types of error may be made. If H 0 is rejected when, in fact, it is true a type 1 error has been committed. If Ho is not true and the test fails to reject it, a type 2 error has been made.

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Hypothesis Testing | A Step-by-Step Guide with Easy Examples

Published on November 8, 2019 by Rebecca Bevans . Revised on June 22, 2023.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics . It is most often used by scientists to test specific predictions, called hypotheses, that arise from theories.

There are 5 main steps in hypothesis testing:

  • State your research hypothesis as a null hypothesis and alternate hypothesis (H o ) and (H a  or H 1 ).
  • Collect data in a way designed to test the hypothesis.
  • Perform an appropriate statistical test .
  • Decide whether to reject or fail to reject your null hypothesis.
  • Present the findings in your results and discussion section.

Though the specific details might vary, the procedure you will use when testing a hypothesis will always follow some version of these steps.

Table of contents

Step 1: state your null and alternate hypothesis, step 2: collect data, step 3: perform a statistical test, step 4: decide whether to reject or fail to reject your null hypothesis, step 5: present your findings, other interesting articles, frequently asked questions about hypothesis testing.

After developing your initial research hypothesis (the prediction that you want to investigate), it is important to restate it as a null (H o ) and alternate (H a ) hypothesis so that you can test it mathematically.

The alternate hypothesis is usually your initial hypothesis that predicts a relationship between variables. The null hypothesis is a prediction of no relationship between the variables you are interested in.

  • H 0 : Men are, on average, not taller than women. H a : Men are, on average, taller than women.

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formulation of hypothesis meaning

For a statistical test to be valid , it is important to perform sampling and collect data in a way that is designed to test your hypothesis. If your data are not representative, then you cannot make statistical inferences about the population you are interested in.

There are a variety of statistical tests available, but they are all based on the comparison of within-group variance (how spread out the data is within a category) versus between-group variance (how different the categories are from one another).

If the between-group variance is large enough that there is little or no overlap between groups, then your statistical test will reflect that by showing a low p -value . This means it is unlikely that the differences between these groups came about by chance.

Alternatively, if there is high within-group variance and low between-group variance, then your statistical test will reflect that with a high p -value. This means it is likely that any difference you measure between groups is due to chance.

Your choice of statistical test will be based on the type of variables and the level of measurement of your collected data .

  • an estimate of the difference in average height between the two groups.
  • a p -value showing how likely you are to see this difference if the null hypothesis of no difference is true.

Based on the outcome of your statistical test, you will have to decide whether to reject or fail to reject your null hypothesis.

In most cases you will use the p -value generated by your statistical test to guide your decision. And in most cases, your predetermined level of significance for rejecting the null hypothesis will be 0.05 – that is, when there is a less than 5% chance that you would see these results if the null hypothesis were true.

In some cases, researchers choose a more conservative level of significance, such as 0.01 (1%). This minimizes the risk of incorrectly rejecting the null hypothesis ( Type I error ).

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The results of hypothesis testing will be presented in the results and discussion sections of your research paper , dissertation or thesis .

In the results section you should give a brief summary of the data and a summary of the results of your statistical test (for example, the estimated difference between group means and associated p -value). In the discussion , you can discuss whether your initial hypothesis was supported by your results or not.

In the formal language of hypothesis testing, we talk about rejecting or failing to reject the null hypothesis. You will probably be asked to do this in your statistics assignments.

However, when presenting research results in academic papers we rarely talk this way. Instead, we go back to our alternate hypothesis (in this case, the hypothesis that men are on average taller than women) and state whether the result of our test did or did not support the alternate hypothesis.

If your null hypothesis was rejected, this result is interpreted as “supported the alternate hypothesis.”

These are superficial differences; you can see that they mean the same thing.

You might notice that we don’t say that we reject or fail to reject the alternate hypothesis . This is because hypothesis testing is not designed to prove or disprove anything. It is only designed to test whether a pattern we measure could have arisen spuriously, or by chance.

If we reject the null hypothesis based on our research (i.e., we find that it is unlikely that the pattern arose by chance), then we can say our test lends support to our hypothesis . But if the pattern does not pass our decision rule, meaning that it could have arisen by chance, then we say the test is inconsistent with our hypothesis .

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

  • Normal distribution
  • Descriptive statistics
  • Measures of central tendency
  • Correlation coefficient

Methodology

  • Cluster sampling
  • Stratified sampling
  • Types of interviews
  • Cohort study
  • Thematic analysis

Research bias

  • Implicit bias
  • Cognitive bias
  • Survivorship bias
  • Availability heuristic
  • Nonresponse bias
  • Regression to the mean

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

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Research Hypothesis In Psychology: Types, & Examples

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A research hypothesis, in its plural form “hypotheses,” is a specific, testable prediction about the anticipated results of a study, established at its outset. It is a key component of the scientific method .

Hypotheses connect theory to data and guide the research process towards expanding scientific understanding

Some key points about hypotheses:

  • A hypothesis expresses an expected pattern or relationship. It connects the variables under investigation.
  • It is stated in clear, precise terms before any data collection or analysis occurs. This makes the hypothesis testable.
  • A hypothesis must be falsifiable. It should be possible, even if unlikely in practice, to collect data that disconfirms rather than supports the hypothesis.
  • Hypotheses guide research. Scientists design studies to explicitly evaluate hypotheses about how nature works.
  • For a hypothesis to be valid, it must be testable against empirical evidence. The evidence can then confirm or disprove the testable predictions.
  • Hypotheses are informed by background knowledge and observation, but go beyond what is already known to propose an explanation of how or why something occurs.
Predictions typically arise from a thorough knowledge of the research literature, curiosity about real-world problems or implications, and integrating this to advance theory. They build on existing literature while providing new insight.

Types of Research Hypotheses

Alternative hypothesis.

The research hypothesis is often called the alternative or experimental hypothesis in experimental research.

It typically suggests a potential relationship between two key variables: the independent variable, which the researcher manipulates, and the dependent variable, which is measured based on those changes.

The alternative hypothesis states a relationship exists between the two variables being studied (one variable affects the other).

A hypothesis is a testable statement or prediction about the relationship between two or more variables. It is a key component of the scientific method. Some key points about hypotheses:

  • Important hypotheses lead to predictions that can be tested empirically. The evidence can then confirm or disprove the testable predictions.

In summary, a hypothesis is a precise, testable statement of what researchers expect to happen in a study and why. Hypotheses connect theory to data and guide the research process towards expanding scientific understanding.

An experimental hypothesis predicts what change(s) will occur in the dependent variable when the independent variable is manipulated.

It states that the results are not due to chance and are significant in supporting the theory being investigated.

The alternative hypothesis can be directional, indicating a specific direction of the effect, or non-directional, suggesting a difference without specifying its nature. It’s what researchers aim to support or demonstrate through their study.

Null Hypothesis

The null hypothesis states no relationship exists between the two variables being studied (one variable does not affect the other). There will be no changes in the dependent variable due to manipulating the independent variable.

It states results are due to chance and are not significant in supporting the idea being investigated.

The null hypothesis, positing no effect or relationship, is a foundational contrast to the research hypothesis in scientific inquiry. It establishes a baseline for statistical testing, promoting objectivity by initiating research from a neutral stance.

Many statistical methods are tailored to test the null hypothesis, determining the likelihood of observed results if no true effect exists.

This dual-hypothesis approach provides clarity, ensuring that research intentions are explicit, and fosters consistency across scientific studies, enhancing the standardization and interpretability of research outcomes.

Nondirectional Hypothesis

A non-directional hypothesis, also known as a two-tailed hypothesis, predicts that there is a difference or relationship between two variables but does not specify the direction of this relationship.

It merely indicates that a change or effect will occur without predicting which group will have higher or lower values.

For example, “There is a difference in performance between Group A and Group B” is a non-directional hypothesis.

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)

It specifies whether one variable is greater, lesser, or different from another, rather than just indicating that there’s a difference without specifying its nature.

For example, “Exercise increases weight loss” is a directional hypothesis.

hypothesis

Falsifiability

The Falsification Principle, proposed by Karl Popper , is a way of demarcating science from non-science. It suggests that for a theory or hypothesis to be considered scientific, it must be testable and irrefutable.

Falsifiability emphasizes that scientific claims shouldn’t just be confirmable but should also have the potential to be proven wrong.

It means that there should exist some potential evidence or experiment that could prove the proposition false.

However many confirming instances exist 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 provide evidence to support a research hypothesis.

Can a Hypothesis be Proven?

Hypotheses make probabilistic predictions. They state the expected outcome if a particular relationship exists. However, a study result supporting a hypothesis does not definitively prove it is true.

All studies have limitations. There may be unknown confounding factors or issues that limit the certainty of conclusions. Additional studies may yield different results.

In science, hypotheses can realistically only be supported with some degree of confidence, not proven. The process of science is to incrementally accumulate evidence for and against hypothesized relationships in an ongoing pursuit of better models and explanations that best fit the empirical data. But hypotheses remain open to revision and rejection if that is where the evidence leads.
  • Disproving a hypothesis is definitive. Solid disconfirmatory evidence will falsify a hypothesis and require altering or discarding it based on the evidence.
  • However, confirming evidence is always open to revision. Other explanations may account for the same results, and additional or contradictory evidence may emerge over time.

We can never 100% prove the alternative hypothesis. Instead, we see if we can disprove, or reject the null hypothesis.

If we reject the null hypothesis, this doesn’t mean that our alternative hypothesis is correct but does support the alternative/experimental hypothesis.

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

  • Identify variables . The researcher manipulates the independent variable and the dependent variable is the measured outcome.
  • Operationalized the variables being investigated . Operationalization 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.
  • Decide on a direction for your prediction . If there is evidence in the literature to support a specific effect of 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.
  • Make it Testable : Ensure your hypothesis can be tested through experimentation or observation. It should be possible to prove it false (principle of falsifiability).
  • Clear & concise language . A strong hypothesis is concise (typically one to two sentences long), and formulated using clear and straightforward language, ensuring it’s easily understood and testable.

Consider a hypothesis many teachers might subscribe to: students work better on Monday morning than on 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 a Friday afternoon and then measuring their immediate recall of 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.

More Examples

  • Memory : Participants exposed to classical music during study sessions will recall more items from a list than those who studied in silence.
  • Social Psychology : Individuals who frequently engage in social media use will report higher levels of perceived social isolation compared to those who use it infrequently.
  • Developmental Psychology : Children who engage in regular imaginative play have better problem-solving skills than those who don’t.
  • Clinical Psychology : Cognitive-behavioral therapy will be more effective in reducing symptoms of anxiety over a 6-month period compared to traditional talk therapy.
  • Cognitive Psychology : Individuals who multitask between various electronic devices will have shorter attention spans on focused tasks than those who single-task.
  • Health Psychology : Patients who practice mindfulness meditation will experience lower levels of chronic pain compared to those who don’t meditate.
  • Organizational Psychology : Employees in open-plan offices will report higher levels of stress than those in private offices.
  • Behavioral Psychology : Rats rewarded with food after pressing a lever will press it more frequently than rats who receive no reward.

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Research Hypothesis: Elements, Format, Types

Research Hypothesis: Elements, Format, Types

When a proposition is formulated for empirical testing, we call it a hypothesis. Almost all studies begin with one or more hypotheses.

Let’s Understand Research Hypothesis.

What is a hypothesis.

A hypothesis, specifically a research hypothesis, is formulated to predict an assumed relationship between two or more variables of interest.

If we reasonably guess that a relationship exists between the variables of interest, we first state it as a hypothesis and then test it in the field.

Hypotheses are stated in terms of the particular dependent and independent variables that are going to be used in the study.

Research Hypothesis Definition

A research hypothesis is a conjectural statement, a logical supposition, a reasonable guess, and an educated prediction about the nature of the relationship between two or more variables that we expect to happen in our study.

Unless you are creating an exploratory study, your hypothesis should always explain what you expect to happen during your experiment or research.

Remember, a hypothesis does not have to be correct. While the hypothesis predicts what the researchers expect to see, the research aims to determine whether this guess is right or wrong.

When experimenting, researchers might explore different factors to determine which ones might contribute to the outcome.

In many cases, researchers may find that the results of an experiment do not support the original hypothesis. When writing up these results, the researchers might suggest other options that should be explored in future studies.

Elements of a Good Hypothesis

Regardless of the type of hypothesis, the goal of a good hypothesis is to help explain the focus and direction of the experiment or research. As such, a good hypothesis will

  • State the purpose of the research.
  • Identify which variables are to be used.

A good hypothesis;

  • Needs to be logical.
  • Must be precise in language.
  • It should be testable with research or experimentation.

A hypothesis is usually written in a form where it proposes that if something is done, then something will occur.

Finally, when you are trying to come up with a good hypothesis for your research or experiments, ask yourself the following questions:

  • Is your hypothesis based on any previous research on a topic?
  • Can your hypothesis be tested?
  • Does your hypothesis include independent and dependent variables?

Before you come up with a specific hypothesis, spend some time doing background research on your topic.

Once you have completed a literature review, start thinking of potential questions you still have. Pay attention to the discussion section in the journal articles you read. Many authors will suggest questions that still need to be explored.

Basic Format of a Good Hypothesis

A hypothesis often follows a basic format of “If {this happens}, then {this will happen}.” One way to structure your hypothesis is to describe what will happen to the dependent variable if you change the independent variable.

The basic format might be:

“If {these changes are made to a certain independent variable}, then we will observe {a change in a specific dependent variable}.”

A few examples:

  • Students who eat breakfast will perform better on a math test than students who do not eat breakfast.
  • Students who experience test anxiety before an exam get higher scores than students who do not experience test anxiety.
  • Drivers who talk on their mobile phones while driving will be more likely to make errors when driving than those who do not talk on the phone.
  • People with high exposure to ultraviolet light will have a higher frequency of skin cancer than those who do not have such exposure.

Look at the last example.

Here is the independent variable (exposure to ultraviolet light)) is specified, and the dependent variable (skin cancer) is also specified.

Notice also that this research hypothesis specifies a direction in that it predicts that people exposed to ultraviolet light will have a higher risk of cancer.

This is not always the case. Research hypotheses can also specify a difference without saying which group will be better or higher than the other.

For example, one might formulate a hypothesis of the type: ‘Religion does not make any significant difference in the performance of cultural activities.’

In general, however, it is considered a better hypothesis if you can specify a direction.

Research hypotheses serve several important functions. The most important one is to direct and guide the research.

A few of the other functions of the research hypothesis are enumerated below:

  • A research hypothesis indicates the major independent variables to be included in the study;
  • A research hypothesis suggests the type of data that must be collected and the type of analysis that must be conducted to measure the relationship;
  • A research hypothesis identifies facts that are relevant and that are not;
  • A research hypothesis suggests the type of research design to be employed.

Types of Research Hypothesis

Two types of research hypotheses are;

  • Descriptive hypothesis.
  • Relational hypothesis.

Descriptive Hypotheses

Descriptive hypotheses are propositions that typically state some variables’ existence, size, form, or distribution.

These hypotheses are formulated in the form of statements in which we assign variables to cases.

For example,

  • The prevalence of contraceptive use among currently married women in India exceeds 60%.

In this example, the case is ‘currently married women,’ and the variable is ‘prevalence of contraceptives.’ As a second example,

  • The public universities are currently experiencing budget difficulties.

Here,’ public universities’ is the case, and ‘budget difficulties’ is the variable.

  • The National Board of Revenue claims that over 15% of potential taxpayers falsify in their income tax returns.
  • At most, 75% of the pre-school children in community A have a protein-deficient diet.
  • The average sales in a superstore exceed taka 25 lac per month.
  • Smoking increases the risk of lung cancer.
  • The average longevity of women is higher among females than among males.
  • Gainfully employed women tend to have lower than average fertility.
  • Women with child loss experience will have higher fertility than those who do not have such experiences.

All examples of descriptive hypotheses.

It is important to note that the Descriptive hypothesis does not always have variables that can be designated as independent or dependent.

Relational Hypotheses

Relational hypotheses, on the other hand, are statements that describe the relationship between variables concerning some cases.

  • Communities with many modern facilities will have a higher rate of contraception than communities with few modern facilities.

In this instance, the case is ‘communities,’ and the variables are ‘rate of contraception’ and ‘modern facilities.’

Similarly, “People who use chewing tobacco have a higher risk of oral carcinoma than people who have never used chewing tobacco” is a relational hypothesis.

A relational hypothesis is again of two types: correlational hypothesis and the causal hypothesis.

A correlational hypothesis states that variables occur in some predictable relationships without implying that one variable causes the other to change or take on different values.

Here is an example of a co-relational hypothesis:

  • Males are more efficient than their female counterparts in typing.

In making such a statement, we do not claim that sex (male-female) as a variable influences the other variable,’ typing efficiency’ (less efficient-more efficient). Here is one more example of a correlational hypothesis:

  • Saving habit is more pronounced among Christians than the people of other religions.

Once again, religion is not believed to be a factor in saving habits, although a positive relationship has been observed.

Look at the following example:

  • The participation of women in household decision making increases with age, their level of education, and the number of surviving children.

Here too, women’s education, several surviving children, or education does not guarantee their decision-making autonomy.

With causal hypotheses (also called explanatory hypotheses), on the other hand, there is an implication that a change in one variable causes a change or leads to an effect on the other variable.

A causal variable is typically called an independent variable, and the other is the dependent variable. It is important to note that the term “cause” roughly means “help make happen.” So, the independent variable need not be the sole reason for the existence of or change in the dependent variable. Here are some examples of causal hypotheses:

  • An increase in family income leads to an increase in the income saved.
  • Exposure of mothers to mass media increases their knowledge of malnutrition among their children.
  • An offer of a discount in a department store enhances the sales volume.
  • Chewing tobacco increases the risk of oral carcinoma.
  • Goat farming contributes to poverty alleviation of rural people.
  • The utilization of child welfare clinics is the lowest in those clinics in which the clinic personnel are poorly motivated to provide preventive services.
  • An increase in bank interest rate encourages the customers for increased savings.

In the above example, we have ample reasons to believe that one variable (family income and savings, misuse of credit, and farm size) has a bearing on the other variable.

We cite two more examples to illustrate the hypothesis, general objective, ultimate objective, and a few specific objectives.

General objective:

  • To compare the complications of acceptors of laparoscopic sterilization and mini-laparotomy among American women.

Research hypothesis:

  • The risk of complications is higher in the mini-laparotomy method of sterilization than in laparoscopic sterilization.

Specific objectives:

  • To assess the complications of laparoscopic sterilization and mini-laparotomy.
  • To assess service providers’ knowledge and perception regarding the complications, preferences, and convenience of the two methods.

Ultimate Objectives:

  • To introduce and popularize the laparoscopic female sterilization method in the National Family Planning Program to reduce the rapid population growth rate.

In a study designed to examine the living and working conditions of the overseas migrant workers from India and the pattern of remittances from overseas migrant workers, the general objective, specific objectives, and the ultimate objective were formulated as follows:

  • To examine the living and working conditions of the overseas migrant workers from India.”
  • Characteristics of migrant workers by significant migration channels;
  • Countries of destination;
  • The occupational skill of the workers;
  • Pattern and procedures of remittances;
  • Impact of remittances on government revenue;
  • Better utilization of remittances.

Ultimate objective:

  • To suggest ways and means to minimize the differences in the policy adopted by the public and private sectors in their recruitment process in the interest of the workers;
  • To ascertain the possible exploitation of the workers by the private agencies and suggest remedies for such exploitation.
  • Private agencies, in most cases, exploit migrant workers.

What are the elements of a good hypothesis?

A good hypothesis should state the purpose of the research, identify which variables are to be used, be logical, precise in language, and be testable with research or experimentation.

How is a hypothesis typically structured?

A hypothesis often follows a basic format of “If {this happens}, then {this will happen}.” It proposes that if something is done, then a specific outcome will occur.

What is a Descriptive hypothesis?

Descriptive hypotheses are propositions that typically state some variables’ existence, size, form, or distribution. They are formulated in the form of statements in which variables are assigned to cases.

What distinguishes a Relational hypothesis?

Relational hypotheses describe the relationship between variables concerning some cases. They can be correlational, where variables occur in a predictable relationship without implying causation, or causal, where a change in one variable causes a change in another.

What is the difference between a correlational hypothesis and a causal hypothesis?

A correlational hypothesis states that variables occur in some predictable relationships without implying that one variable causes the other to change. A causal hypothesis, on the other hand, implies that a change in one variable causes a change or leads to an effect on the other variable.

What are the two main types of research hypotheses?

The two main types of research hypotheses are Descriptive hypothesis and Relational hypothesis

What is a hypothesis in the context of academic research?

A hypothesis is a statement about an expected relationship between variables or an explanation of an occurrence that is clear, specific, and testable.

How does a research hypothesis differ from a general hypothesis?

A research hypothesis is more specific and clear about what’s being assessed and the expected outcome. It must also be testable, meaning there should be a way to prove or disprove it.

What are the essential attributes of a good research hypothesis?

A good research hypothesis should have specificity, clarity, and testability.

Why is testability crucial for a research hypothesis?

Testability ensures that empirical research can prove or disproven the hypothesis. If a statement isn’t testable, it doesn’t qualify as a research hypothesis.

What is the null hypothesis?

The null hypothesis is the counter-proposal to the original hypothesis. It predicts that there is no relationship between the variables in question.

How can one ensure that a hypothesis is clear and specific?

A hypothesis should clearly identify the variables involved, the parties involved, and the expected relationship type, leaving no ambiguity about its intent or meaning.

Why is it essential to avoid value judgments in a research hypothesis?

Value judgments are subjective and not appropriate for a hypothesis. A research hypothesis should strive to be objective, avoiding personal opinions.

What is the basic definition of a hypothesis in research?

A research hypothesis is a statement about an expected relationship between variables, or an explanation of an occurrence, that is clear, specific, and testable.

While a general hypothesis is an idea or explanation based on known facts but not yet proven, a research hypothesis is a clear, specific, and testable statement about the expected outcome of a study.

What are the essential characteristics of a good research hypothesis?

A good research hypothesis should possess specificity, clarity, and testability. It should clearly define what’s being assessed and the expected outcome, and it must be possible to prove or disprove the statement through experimentation.

How can one ensure that a hypothesis is testable?

A hypothesis is testable if there’s a possibility to prove both its truth and falsity. The results of the hypothesis should be reproducible, and it should be specific enough to allow for clear testing procedures.

What is the difference between a null hypothesis and an alternative hypothesis?

The null hypothesis proposes that no statistical significance exists in a set of observations, suggesting any differences are due to chance alone. The alternative hypothesis, on the other hand, predicts a relationship between the variables of the study and states that the results are significant to the research topic.

How should one formulate an effective research hypothesis?

To formulate an effective research hypothesis, one should state the problem clearly, use an ‘if-then’ statement structure, define the variables as dependent or independent, and scrutinize the hypothesis to ensure it meets the criteria of specificity, clarity, and testability.

What are some types of hypotheses in research?

Types of hypotheses include simple, complex, directional, non-directional, associative and causal, empirical, and statistical hypotheses. Each type serves a specific purpose and is used based on the nature of the research question or problem.

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Hypothesis: meaning, criteria for formulation and it’s types.

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Read this article to learn about the meaning, criteria for formulation and types of hypothesis.

Meaning of Hypothesis:

In order to make the problem explicit and in order to focus attention in its solution, it is essential to start with certain known theories. Research, in real terms, depends upon a continuous interplay of theory and facts, upon a continuous stimulation of facts by theory and theory by facts. Theory is initiated by facts and facts lead to the rejection or reformulation of existing theory. Facts may also redefine or clarify the theory.

Hampel has compared a scientific theory to a network in which the terms and concepts are represented by knots and definitions and hypothesis by threads connecting the knots. From certain observational data we derive an interpretative string to some points in the theoretical framework. Then we proceed through definitions and hypothesis to other points from which another interpretative string permits to the plane of observation.

Theory thus gives meaning to empirically observed facts and puts them systematically. Theory is also built upon facts and various facts put in a theoretically framework may be analyzed and interpreted in a logical manner. Grounded on old facts and with the help of theoretical framework, new facts are discovered. In the process, certain deductions are formulated which are called hypotheses.

Thus “after internalizing the problem, after turning back on experience for possible solutions, after observing relevant phenomena, the scientist may formulate a hypothesis.” “A Hypothesis is a conjectural statement, a tentative proposition about relation between two or more phenomena or variables”. It is a tentative generalization, the validity of which remains to be tested.

At its initial stage, a hypothesis may be an imagined idea or a hunch or a mere guess. It is in the form of a declarative sentence and always indicates relation of one or more variable(s) with other variable(s) in a general or specific way. It is mostly based on accumulated knowledge. A hypothesis is made to examine the correct explanation of a phenomenon through investigation, to observe facts on the basis of collected data. If on the basis of verification, the hypothesis is found to be valid, a theory is obtained. Thus, hypothesis a theory entertained in order to study the facts and find out the validity of the theory.

The etymological meaning of hypothesis, therefore, is a theory which is not full reasoned, derived out of the combination of two words ‘hypo’ and ‘thesis’ meaning ‘less than’ and ‘reasoned theory of rational view point’ respectively. Accordingly Mill defines hypothesis as “any supposition which we make (either without actual evidence or an evidence avowedly insufficient) in order to endeavor to deduce conclusions in accordance with facts which are known to be real, under the idea that if the conclusions to which the hypothesis leads are known truths, the hypothesis itself either must be or at least likely to be, true”. Likewise, Goode and Hatt define it as “a proposition which can be put to test to determine validity”.

P.V. Young says that a hypothesis “is provisional central idea which becomes the basis for fruitful investigation, known as working theory” Coffey defines hypothesis as “an attempt at explanation : a provisional supposition made in order to explain scientifically some facts or phenomena”. Hypothesis is not a theory; rather hypotheses are linked and related to theory which is more elaborate in nature as compared to hypothesis.

Therefore William H. George, while distinguishing between theory and hypothesis, described theory as ‘elaborate hypothesis’. Hypothesis is not a claim of truth, but a claim for truth and hence serves as a bridge in the process of investigation which begins with a problem and ends with resolution of the problem. In the words of Cohen and Nagel “a hypothesis directs our search for the order.”

Criteria for Formulation of Hypothesis :

There exist two criteria for formulation of a good hypothesis. First, it is a statement about the relations between variables. Secondly it carries clear implications for testing the stated relations. Thus, these couple of criteria imply that the hypotheses comprise two or more variables which are measurable or potentially measurable and that they specify the way in which they are related. A statement which fails to meet these criteria is no scientific hypothesis in the true sense of the term. However, there are legitimate hypotheses, formulated in factor analytic studies.

The following examples may be cited in order to justify how the couple of criteria apply to hypotheses:

1. More intelligent persons will be less hostile than those of lower level of intelligence.

2. Group study contributes to higher grade achievement.

In the first hypothesis, we visualize a relation stated between one variable, ‘intelligence’, and another variable ‘hostility.’ Furthermore, measurement of these variables is also easily conceivable. In the second example, a relation has also been stated between the variables ‘group study’ and ‘grade achievement.’ There exists the possibility of the measurement of the variables are thus there is implication for testing the hypotheses. Thus both the criteria are satisfied. ‘

Types of Hypothesis :

Hypotheses may be of various kinds. It may be crude or refined. A crude hypothesis is at the lower level of abstraction, indicating only the kind of data to be collected, not leading to higher theoretical research. On the contrary, the refined hypothesis appears to be more significant in research.

It may be in the form of describing something in a given instance, that a particular object, situation or event has certain characteristics. It may be in the form of counting the frequencies or of association among the variables. It may be in the form of causal relationship that a particular characteristic or occurrence is one of the causes determining the other.

On the basis of levels of abstraction, Goode and Hatt have distinguished three broad types of hypotheses.

First, there are the simple levels of hypotheses indicating merely the uniformity in social behaviour. They are the most exact and the least abstract, as they state the existence of presence of empirical uniformities. Often it is said that such hypotheses do not involve much verification or do not require testing at all and they merely add up facts. But it is not correct to say so. Even empirical researches describing certain facts need testing of hypotheses and testing may result in providing with an altogether different profile.

Secondly, there are complex ideal hypotheses at a higher level of abstraction. These are more complex and aim at testing the existence of logically derived relationships between empirical uniformities. They are in the form of generalization, and therefore are also a little abstract. But empirical relationships are important in their context. Such hypotheses are useful in developing tools of analysis and in providing constructs for further hypothesizing.

Thirdly, there are hypotheses which are very complex and quite abstract. They are concerned with the interrelations of multiple analytic variables. They lead to the formulation of a relationship between changes in one property and changes in another.

The above kinds of hypotheses may be explained in an example. On the basis of empirical data we may show statistical regularity by wealth, religion region, size of community culture, tradition, health etc. First, we may formulate hypotheses in a simple manner on the basis of statistical regularity. Secondly, in order to formulate a complex ideal hypothesis we may combine all the factors together. As regards the formulation of the third category of hypothesis, more abstraction is brought in.

Only one of the factors can be studied at a time, such as relationship between religion and fertility or wealth and fertility, and all other variables may be controlled. Obviously, it is a very abstract way of handling the problem, because people may be affected by a multiplicity of variables. Yet, we are interested in studying the cause and effect relationship of one factor at one time. Hence, this level of hypothesizing is not only more abstract, simultaneously it is more sophisticated and provides scope for further research.

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  • Scientific Methods

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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  2. How to Write a Strong Hypothesis

    Home Knowledge Base Methodology How to Write a Strong Hypothesis | Steps & Examples How to Write a Strong Hypothesis | Steps & Examples Published on May 6, 2022 by Shona McCombes . Revised on November 20, 2023. A hypothesis is a statement that can be tested by scientific research.

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    The formulation and testing of a hypothesis is part of the scientific method, the approach scientists use when attempting to understand and test ideas about natural phenomena. The generation of a hypothesis frequently is described as a creative process and is based on existing scientific knowledge, intuition, or experience.

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  5. What is a Research Hypothesis: How to Write it, Types, and Examples

    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.

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    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.

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    Step 1: Ask a question Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project. Example: Research question Do students who attend more lectures get better exam results? Step 2: Do some preliminary research

  8. PDF 1. Formulation of Research Hypothesis with student samples

    Your hypothesis is what you propose to "prove" by your research. As a result of your research, you will arrive at a conclusion, a theory, or understanding that will be useful or applicable beyond the research itself. 3. Avoid judgmental words in your hypothesis. Value judgments are subjective and are not appropriate for a hypothesis.

  9. What is a Research Hypothesis and How to Write a Hypothesis

    The steps to write a research hypothesis are: 1. Stating the problem: Ensure that the hypothesis defines the research problem 2. Writing a hypothesis as an 'if-then' statement: Include the action and the expected outcome of your study by following a 'if-then' structure. 3.

  10. What Is A Research Hypothesis? A Simple Definition

    A research hypothesis (also called a scientific hypothesis) is a statement about the expected outcome of a study (for example, a dissertation or thesis). To constitute a quality hypothesis, the statement needs to have three attributes - specificity, clarity and testability. Let's take a look at these more closely.

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    Based on your knowledge of human physiology, you formulate a hypothesis that men are, on average, taller than women. To test this hypothesis, you restate it as: H 0: Men are, on average, not taller than women. H a: Men are, on average, taller than women. The only proofreading tool specialized in correcting academic writing - try for free!

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