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How Do You Write a Hypothesis for a Research Paper: Tips and Examples

Crafting a well-defined hypothesis is a critical step in the research process, serving as the foundation for your study. A hypothesis not only guides your research design but also provides a clear focus for your investigation. In this article, we will explore the essential aspects of writing a strong hypothesis for a research paper, including its characteristics, formulation steps, types, and common pitfalls to avoid. Additionally, we will provide examples from various disciplines to illustrate what makes a hypothesis effective.

Key Takeaways

• A hypothesis is a testable statement that predicts the relationship between variables in your research.
• Clarity and precision are crucial for a strong hypothesis, ensuring that it is understandable and specific.
• A good hypothesis must be testable and falsifiable, meaning it can be supported or refuted through experimentation or observation.
• Formulating a hypothesis involves identifying a research problem, conducting a literature review, and clearly stating the expected outcome.
• Avoid common pitfalls such as overly complex hypotheses, vague language, and lack of testability to ensure your hypothesis is effective.

Understanding the Role of a Hypothesis in Research

Defining a hypothesis.

A hypothesis is a testable prediction about the relationship between two or more variables. It serves as a navigational tool in the research process, directing what you aim to predict and how. Crafting a thesis statement is crucial in the writing process, guiding research and shaping arguments.

Purpose and Importance of a Hypothesis

In research, a hypothesis serves as the cornerstone for your empirical study. It not only lays out what you aim to investigate but also provides a structured approach for your data collection and analysis. Flexibility and clarity are key for effective statements.

Hypothesis vs. Prediction

A hypothesis is an attempt at explaining a phenomenon or the relationships between phenomena/variables in the real world. While hypotheses are sometimes called “educated guesses,” they should be based on previous observations, existing theories, scientific evidence, and logic. A hypothesis is not a prediction; rather, predictions are based on clearly formulated hypotheses.

Key Characteristics of a Strong Hypothesis

A robust hypothesis is essential for guiding your research effectively. Firstly, clarity and precision are paramount . Your hypothesis should be specific and unambiguous, providing a clear understanding of the expected relationship between variables. This ensures that your research question is well-defined and comprehensible.

Testability and falsifiability are also crucial. A hypothesis must be testable, allowing you to analyze data through empirical means, such as observation or experimentation, to assess if there is significant support for the hypothesis. Additionally, it should be falsifiable, meaning that it can be proven wrong through evidence.

Lastly, relevance to the research question is vital. Your hypothesis should be grounded in existing research or theoretical frameworks, ensuring its applicability and significance to the field of study. This connection to prior research not only strengthens your hypothesis but also aligns it with the broader academic discourse.

Steps to Formulate a Hypothesis for a Research Paper

Identifying the research problem.

The first step in formulating a hypothesis is to clearly identify the research problem. This involves understanding the phenomenon or the relationships between variables that you wish to explore. A well-defined research problem sets the stage for a focused and effective hypothesis.

Conducting a Literature Review

Before you can formulate a hypothesis, it's essential to conduct a thorough literature review. This helps you understand what has already been studied and where gaps in the research exist. By reviewing existing literature, you can ensure that your hypothesis is both original and relevant.

Formulating the Hypothesis

Once you have identified the research problem and reviewed the literature, you can begin to formulate your hypothesis . A strong hypothesis should be clear, testable, and directly related to the research question. It often helps to frame your hypothesis as an 'if-then' statement, which clearly outlines the expected relationship between variables.

Types of Hypotheses in Research

Understanding the various types of hypotheses is crucial for crafting effective research. Each type serves a unique purpose and can significantly influence the direction and outcomes of your study. All hypotheses contrast with the null hypothesis , which posits that no significant relationship exists between the variables under investigation.

Common Pitfalls to Avoid When Writing a Hypothesis

When crafting a hypothesis for your research paper, it's crucial to steer clear of common mistakes that can undermine your work. Avoiding these pitfalls will help you create a robust and testable hypothesis that can withstand academic scrutiny.

Examples of Well-Written Hypotheses

In this section, we will explore various examples of well-crafted hypotheses to help you understand what makes a hypothesis strong and effective. By examining these examples, you can gain insights into the essential components that contribute to a robust hypothesis.

Testing and Refining Your Hypothesis

Once you have formulated your hypothesis, the next crucial step is to test and refine it. This process ensures that your hypothesis is robust and reliable, ultimately contributing to the validity of your research findings.

Testing and refining your hypothesis is a crucial step in your thesis journey. It ensures that your research is on the right track and that your findings are valid. To make this process easier, our Thesis Action Plan offers a structured approach to help you navigate through each stage with confidence. Don't let uncertainty hold you back. Visit our website to learn more and claim your special offer now !

Crafting a well-defined hypothesis is a critical step in the research process, serving as the foundation upon which your entire study is built. A clear and concise hypothesis not only guides your research design and methodology but also provides a focal point for data collection and analysis. By following the tips and examples provided in this article, researchers can develop robust hypotheses that are both testable and meaningful. Remember, a strong hypothesis is characterized by its specificity, clarity, and relevance to the research question. As you embark on your research journey, take the time to refine your hypothesis, as it will significantly impact the quality and credibility of your study. With careful consideration and thoughtful formulation, your hypothesis can pave the way for insightful and impactful research findings.

Frequently Asked Questions

What is a hypothesis in a research paper.

A hypothesis in a research paper is a statement that predicts the relationship between variables. It serves as a tentative explanation for an observation, phenomenon, or scientific problem that can be tested by further investigation.

How do I formulate a strong hypothesis?

To formulate a strong hypothesis, ensure it is clear, precise, testable, and relevant to your research question. Conducting a thorough literature review can help you identify gaps in existing knowledge and formulate a hypothesis that addresses those gaps.

What is the difference between a hypothesis and a prediction?

A hypothesis is a testable statement about the relationship between two or more variables, while a prediction is a specific outcome that you expect to observe if the hypothesis is true. Predictions are often derived from hypotheses.

What are the types of hypotheses in research?

The main types of hypotheses in research are the null hypothesis, alternative hypothesis, directional hypothesis, and non-directional hypothesis. Each type serves a different purpose in statistical testing and research design.

Why is testability important in a hypothesis?

Testability is crucial in a hypothesis because it allows researchers to use empirical methods to determine whether the hypothesis is supported or refuted by the data. A hypothesis must be testable to be scientifically valid.

Can a hypothesis be revised?

Yes, a hypothesis can be revised based on new data, insights, or changes in the research focus. Revising a hypothesis is a common part of the scientific process as researchers refine their questions and methods.

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Step-by-Step Guide: How to Craft a Strong Research Hypothesis

• 4 minute read
• 384.4K views

Table of Contents

A research hypothesis is a concise statement about the expected result of an experiment or project. In many ways, a research hypothesis represents the starting point for a scientific endeavor, as it establishes a tentative assumption that is eventually substantiated or falsified, ultimately improving our certainty about the subject investigated.   

To help you with this and ease the process, in this article, we discuss the purpose of research hypotheses and list the most essential qualities of a compelling hypothesis. Let’s find out!  

How to Craft a Research Hypothesis  

Crafting a research hypothesis begins with a comprehensive literature review to identify a knowledge gap in your field. Once you find a question or problem, come up with a possible answer or explanation, which becomes your hypothesis. Now think about the specific methods of experimentation that can prove or disprove the hypothesis, which ultimately lead to the results of the study.   

Enlisted below are some standard formats in which you can formulate a hypothesis¹ :  

• A hypothesis can use the if/then format when it seeks to explore the correlation between two variables in a study primarily.  

Example: If administered drug X, then patients will experience reduced fatigue from cancer treatment.  

• A hypothesis can adopt when X/then Y format when it primarily aims to expose a connection between two variables  

Example: When workers spend a significant portion of their waking hours in sedentary work , then they experience a greater frequency of digestive problems.  

• A hypothesis can also take the form of a direct statement.  

Example: Drug X and drug Y reduce the risk of cognitive decline through the same chemical pathways  

What are the Features of an Effective Hypothesis?  

Hypotheses in research need to satisfy specific criteria to be considered scientifically rigorous. Here are the most notable qualities of a strong hypothesis:  

• Testability: Ensure the hypothesis allows you to work towards observable and testable results.  
• Brevity and objectivity: Present your hypothesis as a brief statement and avoid wordiness.  
• Clarity and Relevance: The hypothesis should reflect a clear idea of what we know and what we expect to find out about a phenomenon and address the significant knowledge gap relevant to a field of study.   

Understanding Null and Alternative Hypotheses in Research  

There are two types of hypotheses used commonly in research that aid statistical analyses. These are known as the null hypothesis and the alternative hypothesis . A null hypothesis is a statement assumed to be factual in the initial phase of the study.   

For example, if a researcher is testing the efficacy of a new drug, then the null hypothesis will posit that the drug has no benefits compared to an inactive control or placebo . Suppose the data collected through a drug trial leads a researcher to reject the null hypothesis. In that case, it is considered to substantiate the alternative hypothesis in the above example, that the new drug provides benefits compared to the placebo.  

Let’s take a closer look at the null hypothesis and alternative hypothesis with two more examples:  

Null Hypothesis:  

The rate of decline in the number of species in habitat X in the last year is the same as in the last 100 years when controlled for all factors except the recent wildfires.  

In the next experiment, the researcher will experimentally reject this null hypothesis in order to confirm the following alternative hypothesis :  

The rate of decline in the number of species in habitat X in the last year is different from the rate of decline in the last 100 years when controlled for all factors other than the recent wildfires.  

In the pair of null and alternative hypotheses stated above, a statistical comparison of the rate of species decline over a century and the preceding year will help the research experimentally test the null hypothesis, helping to draw scientifically valid conclusions about two factors—wildfires and species decline.   

We also recommend that researchers pay attention to contextual echoes and connections when writing research hypotheses. Research hypotheses are often closely linked to the introduction ² , such as the context of the study, and can similarly influence the reader’s judgment of the relevance and validity of the research hypothesis.  

Seasoned experts, such as professionals at Elsevier Language Services, guide authors on how to best embed a hypothesis within an article so that it communicates relevance and credibility. Contact us if you want help in ensuring readers find your hypothesis robust and unbiased.  

References  

• Hypotheses – The University Writing Center. (n.d.). https://writingcenter.tamu.edu/writing-speaking-guides/hypotheses  
• Shaping the research question and hypothesis. (n.d.). Students. https://students.unimelb.edu.au/academic-skills/graduate-research-services/writing-thesis-sections-part-2/shaping-the-research-question-and-hypothesis  

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• How to Write a Strong Hypothesis | Guide & Examples

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 .

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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.

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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McCombes, S. (2022, May 06). How to Write a Strong Hypothesis | Guide & Examples. Scribbr. Retrieved 23 September 2024, from https://www.scribbr.co.uk/research-methods/hypothesis-writing/

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

Any research begins with a research question and a research hypothesis . A research question alone may not suffice to design the experiment(s) needed to answer it. A hypothesis is central to the scientific method. But what is a hypothesis ? A hypothesis is a testable statement that proposes a possible explanation to a phenomenon, and it may include a prediction. Next, you may ask what is a research hypothesis ? Simply put, a research hypothesis is a prediction or educated guess about the relationship between the variables that you want to investigate.  

It is important to be thorough when developing your research hypothesis. Shortcomings in the framing of a hypothesis can affect the study design and the results. A better understanding of the research hypothesis definition and characteristics of a good hypothesis will make it easier for you to develop your own hypothesis for your research. Let’s dive in to know more about the types of research hypothesis , how to write a research hypothesis , and some research hypothesis examples .  

Table of Contents

What is a hypothesis ?  

A hypothesis is based on the existing body of knowledge in a study area. Framed before the data are collected, a hypothesis states the tentative relationship between independent and dependent variables, along with a prediction of the outcome.  

What is a research hypothesis ?  

Young researchers starting out their journey are usually brimming with questions like “ What is a hypothesis ?” “ What is a research hypothesis ?” “How can I write a good research hypothesis ?”   

A research hypothesis is a statement that proposes a possible explanation for an observable phenomenon or pattern. It guides the direction of a study and predicts the outcome of the investigation. A research hypothesis is testable, i.e., it can be supported or disproven through experimentation or observation.     

Characteristics of a good hypothesis  

Here are the characteristics of a good hypothesis :  

• Clearly formulated and free of language errors and ambiguity  
• Concise and not unnecessarily verbose  
• Has clearly defined variables  
• Testable and stated in a way that allows for it to be disproven  
• Can be tested using a research design that is feasible, ethical, and practical   
• Specific and relevant to the research problem  
• Rooted in a thorough literature search  
• Can generate new knowledge or understanding.  

How to create an effective research hypothesis  

A study begins with the formulation of a research question. A researcher then performs background research. This background information forms the basis for building a good research hypothesis . The researcher then performs experiments, collects, and analyzes the data, interprets the findings, and ultimately, determines if the findings support or negate the original hypothesis.  

Let’s look at each step for creating an effective, testable, and good research hypothesis :  

• Identify a research problem or question: Start by identifying a specific research problem.   
• Review the literature: Conduct an in-depth review of the existing literature related to the research problem to grasp the current knowledge and gaps in the field.   
• Formulate a clear and testable hypothesis : Based on the research question, use existing knowledge to form a clear and testable hypothesis . The hypothesis should state a predicted relationship between two or more variables that can be measured and manipulated. Improve the original draft till it is clear and meaningful.  
• State the null hypothesis: The null hypothesis is a statement that there is no relationship between the variables you are studying.   
• Define the population and sample: Clearly define the population you are studying and the sample you will be using for your research.  
• Select appropriate methods for testing the hypothesis: Select appropriate research methods, such as experiments, surveys, or observational studies, which will allow you to test your research hypothesis .  

Remember that creating a research hypothesis is an iterative process, i.e., you might have to revise it based on the data you collect. You may need to test and reject several hypotheses before answering the research problem.  

How to write a research hypothesis  

When you start writing a research hypothesis , you use an “if–then” statement format, which states the predicted relationship between two or more variables. Clearly identify the independent variables (the variables being changed) and the dependent variables (the variables being measured), as well as the population you are studying. Review and revise your hypothesis as needed.  

An example of a research hypothesis in this format is as follows:  

“ If [athletes] follow [cold water showers daily], then their [endurance] increases.”  

Population: athletes  

Independent variable: daily cold water showers  

Dependent variable: endurance  

You may have understood the characteristics of a good hypothesis . But note that a research hypothesis is not always confirmed; a researcher should be prepared to accept or reject the hypothesis based on the study findings.  

Research hypothesis checklist  

Following from above, here is a 10-point checklist for a good research hypothesis :  

• Testable: A research hypothesis should be able to be tested via experimentation or observation.  
• Specific: A research hypothesis should clearly state the relationship between the variables being studied.  
• Based on prior research: A research hypothesis should be based on existing knowledge and previous research in the field.  
• Falsifiable: A research hypothesis should be able to be disproven through testing.  
• Clear and concise: A research hypothesis should be stated in a clear and concise manner.  
• Logical: A research hypothesis should be logical and consistent with current understanding of the subject.  
• Relevant: A research hypothesis should be relevant to the research question and objectives.  
• Feasible: A research hypothesis should be feasible to test within the scope of the study.  
• Reflects the population: A research hypothesis should consider the population or sample being studied.  
• Uncomplicated: A good research hypothesis is written in a way that is easy for the target audience to understand.  

By following this research hypothesis checklist , you will be able to create a research hypothesis that is strong, well-constructed, and more likely to yield meaningful results.  

Types of research hypothesis  

Different types of research hypothesis are used in scientific research:  

1. Null hypothesis:

A null hypothesis states that there is no change in the dependent variable due to changes to the independent variable. This means that the results are due to chance and are not significant. A null hypothesis is denoted as H0 and is stated as the opposite of what the alternative hypothesis states.   

Example: “ The newly identified virus is not zoonotic .”  

2. Alternative hypothesis:

This states that there is a significant difference or relationship between the variables being studied. It is denoted as H1 or Ha and is usually accepted or rejected in favor of the null hypothesis.  

Example: “ The newly identified virus is zoonotic .”  

3. Directional hypothesis :

This specifies the direction of the relationship or difference between variables; therefore, it tends to use terms like increase, decrease, positive, negative, more, or less.   

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

4. Non-directional hypothesis:

While it does not predict the exact direction or nature of the relationship between the two variables, a non-directional hypothesis states the existence of a relationship or difference between variables but not the direction, nature, or magnitude of the relationship. A non-directional hypothesis may be used when there is no underlying theory or when findings contradict previous research.  

Example, “ Cats and dogs differ in the amount of affection they express .”  

5. Simple hypothesis :

A simple hypothesis only predicts the relationship between one independent and another independent variable.  

Example: “ Applying sunscreen every day slows skin aging .”  

6 . Complex hypothesis :

A complex hypothesis states the relationship or difference between two or more independent and dependent variables.   

Example: “ Applying sunscreen every day slows skin aging, reduces sun burn, and reduces the chances of skin cancer .” (Here, the three dependent variables are slowing skin aging, reducing sun burn, and reducing the chances of skin cancer.)  

7. Associative hypothesis:  

An associative hypothesis states that a change in one variable results in the change of the other variable. The associative hypothesis defines interdependency between variables.  

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

8 . Causal hypothesis:

A causal hypothesis proposes a cause-and-effect interaction between variables.  

Example: “ Long-term alcohol use causes liver damage .”  

Note that some of the types of research hypothesis mentioned above might overlap. The types of hypothesis chosen will depend on the research question and the objective of the study.  

Research hypothesis examples  

Here are some good research hypothesis examples :  

“The use of a specific type of therapy will lead to a reduction in symptoms of depression in individuals with a history of major depressive disorder.”  

“Providing educational interventions on healthy eating habits will result in weight loss in overweight individuals.”  

“Plants that are exposed to certain types of music will grow taller than those that are not exposed to music.”  

“The use of the plant growth regulator X will lead to an increase in the number of flowers produced by plants.”  

Characteristics that make a research hypothesis weak are unclear variables, unoriginality, being too general or too vague, and being untestable. A weak hypothesis leads to weak research and improper methods.   

Some bad research hypothesis examples (and the reasons why they are “bad”) are as follows:  

“This study will show that treatment X is better than any other treatment . ” (This statement is not testable, too broad, and does not consider other treatments that may be effective.)  

“This study will prove that this type of therapy is effective for all mental disorders . ” (This statement is too broad and not testable as mental disorders are complex and different disorders may respond differently to different types of therapy.)  

“Plants can communicate with each other through telepathy . ” (This statement is not testable and lacks a scientific basis.)  

Importance of testable hypothesis  

If a research hypothesis is not testable, the results will not prove or disprove anything meaningful. The conclusions will be vague at best. A testable hypothesis helps a researcher focus on the study outcome and understand the implication of the question and the different variables involved. A testable hypothesis helps a researcher make precise predictions based on prior research.  

To be considered testable, there must be a way to prove that the hypothesis is true or false; further, the results of the hypothesis must be reproducible.  

Frequently Asked Questions (FAQs) on research hypothesis  

1. What is the difference between research question and research hypothesis ?  

A research question defines the problem and helps outline the study objective(s). It is an open-ended statement that is exploratory or probing in nature. Therefore, it does not make predictions or assumptions. It helps a researcher identify what information to collect. A research hypothesis , however, is a specific, testable prediction about the relationship between variables. Accordingly, it guides the study design and data analysis approach.

2. When to reject null hypothesis ?

A null hypothesis should be rejected when the evidence from a statistical test shows that it is unlikely to be true. This happens when the test statistic (e.g., p -value) is less than the defined significance level (e.g., 0.05). Rejecting the null hypothesis does not necessarily mean that the alternative hypothesis is true; it simply means that the evidence found is not compatible with the null hypothesis.  

3. How can I be sure my hypothesis is testable?  

A testable hypothesis should be specific and measurable, and it should state a clear relationship between variables that can be tested with data. To ensure that your hypothesis is testable, consider the following:  

• Clearly define the key variables in your hypothesis. You should be able to measure and manipulate these variables in a way that allows you to test the hypothesis.  
• The hypothesis should predict a specific outcome or relationship between variables that can be measured or quantified.   
• You should be able to collect the necessary data within the constraints of your study.  
• It should be possible for other researchers to replicate your study, using the same methods and variables.   
• Your hypothesis should be testable by using appropriate statistical analysis techniques, so you can draw conclusions, and make inferences about the population from the sample data.  
• The hypothesis should be able to be disproven or rejected through the collection of data.  

4. How do I revise my research hypothesis if my data does not support it?  

If your data does not support your research hypothesis , you will need to revise it or develop a new one. You should examine your data carefully and identify any patterns or anomalies, re-examine your research question, and/or revisit your theory to look for any alternative explanations for your results. Based on your review of the data, literature, and theories, modify your research hypothesis to better align it with the results you obtained. Use your revised hypothesis to guide your research design and data collection. It is important to remain objective throughout the process.  

5. I am performing exploratory research. Do I need to formulate a research hypothesis?  

As opposed to “confirmatory” research, where a researcher has some idea about the relationship between the variables under investigation, exploratory research (or hypothesis-generating research) looks into a completely new topic about which limited information is available. Therefore, the researcher will not have any prior hypotheses. In such cases, a researcher will need to develop a post-hoc hypothesis. A post-hoc research hypothesis is generated after these results are known.  

6. How is a research hypothesis different from a research question?

A research question is an inquiry about a specific topic or phenomenon, typically expressed as a question. It seeks to explore and understand a particular aspect of the research subject. In contrast, a research hypothesis is a specific statement or prediction that suggests an expected relationship between variables. It is formulated based on existing knowledge or theories and guides the research design and data analysis.

7. Can a research hypothesis change during the research process?

Yes, research hypotheses can change during the research process. As researchers collect and analyze data, new insights and information may emerge that require modification or refinement of the initial hypotheses. This can be due to unexpected findings, limitations in the original hypotheses, or the need to explore additional dimensions of the research topic. Flexibility is crucial in research, allowing for adaptation and adjustment of hypotheses to align with the evolving understanding of the subject matter.

8. How many hypotheses should be included in a research study?

The number of research hypotheses in a research study varies depending on the nature and scope of the research. It is not necessary to have multiple hypotheses in every study. Some studies may have only one primary hypothesis, while others may have several related hypotheses. The number of hypotheses should be determined based on the research objectives, research questions, and the complexity of the research topic. It is important to ensure that the hypotheses are focused, testable, and directly related to the research aims.

9. Can research hypotheses be used in qualitative research?

Yes, research hypotheses can be used in qualitative research, although they are more commonly associated with quantitative research. In qualitative research, hypotheses may be formulated as tentative or exploratory statements that guide the investigation. Instead of testing hypotheses through statistical analysis, qualitative researchers may use the hypotheses to guide data collection and analysis, seeking to uncover patterns, themes, or relationships within the qualitative data. The emphasis in qualitative research is often on generating insights and understanding rather than confirming or rejecting specific research hypotheses through statistical testing.

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The Craft of Writing a Strong Hypothesis

Table of Contents

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

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

What is a Hypothesis?

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

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

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

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

Different Types of Hypotheses‌

Types of hypotheses

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

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

1. Null hypothesis

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

2. Alternative hypothesis

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

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

3. Simple hypothesis

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

4. Complex hypothesis

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

5. Associative and casual hypothesis

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

6. Empirical hypothesis

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

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

7. Statistical hypothesis

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

Characteristics of a Good Hypothesis

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

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

Separating a Hypothesis from a Prediction

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

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

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

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

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

Finally, How to Write a Hypothesis

Quick tips on writing a hypothesis

1.  Be clear about your research question

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

2. Carry out a recce

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

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

3. Create a 3-dimensional hypothesis

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

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

4. Write the first draft

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

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

5. Proof your hypothesis

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

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

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

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

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

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

Frequently Asked Questions (FAQs)

1. what is the definition of hypothesis.

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

2. What is an example of hypothesis?

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

3. What is an example of null hypothesis?

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

4. What are the types of research?

• Fundamental research

• Applied research

• Qualitative research

• Quantitative research

• Mixed research

• Exploratory research

• Longitudinal research

• Cross-sectional research

• Field research

• Laboratory research

• Fixed research

• Flexible research

• Action research

• Policy research

• Classification research

• Comparative research

• Causal research

• Inductive research

• Deductive research

5. How to write a hypothesis?

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

• Avoid wordiness by keeping it simple and brief.

• Your hypothesis should contain observable and testable outcomes.

• Your hypothesis should be relevant to the research question.

6. What are the 2 types of hypothesis?

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

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

7. Difference between research question and research hypothesis?

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

8. What is plural for hypothesis?

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

9. What is the red queen hypothesis?

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

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

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

11. When to reject null hypothesis?

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

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How to write a research hypothesis

Last updated

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Reviewed by

Miroslav Damyanov

Start with a broad subject matter that excites you, so your curiosity will motivate your work. Conduct a literature search to determine the range of questions already addressed and spot any holes in the existing research.

Narrow the topics that interest you and determine your research question. Rather than focusing on a hole in the research, you might choose to challenge an existing assumption, a process called problematization. You may also find yourself with a short list of questions or related topics.

Use the FINER method to determine the single problem you'll address with your research. FINER stands for:

I nteresting

You need a feasible research question, meaning that there is a way to address the question. You should find it interesting, but so should a larger audience. Rather than repeating research that others have already conducted, your research hypothesis should test something novel or unique. 

The research must fall into accepted ethical parameters as defined by the government of your country and your university or college if you're an academic. You'll also need to come up with a relevant question since your research should provide a contribution to the existing research area.

This process typically narrows your shortlist down to a single problem you'd like to study and the variable you want to test. You're ready to write your hypothesis statements.

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• Types of research hypotheses

It is important to narrow your topic down to one idea before trying to write your research hypothesis. You'll only test one problem at a time. To do this, you'll write two hypotheses – a null hypothesis (H0) and an alternative hypothesis (Ha).

You'll come across many terms related to developing a research hypothesis or referring to a specific type of hypothesis. Let's take a quick look at these terms.

Null hypothesis

The term null hypothesis refers to a research hypothesis type that assumes no statistically significant relationship exists within a set of observations or data. It represents a claim that assumes that any observed relationship is due to chance. Represented as H0, the null represents the conjecture of the research.

Alternative hypothesis

The alternative hypothesis accompanies the null hypothesis. It states that the situation presented in the null hypothesis is false or untrue, and claims an observed effect in your test. This is typically denoted by Ha or H(n), where “n” stands for the number of alternative hypotheses. You can have more than one alternative hypothesis. 

Simple hypothesis

The term simple hypothesis refers to a hypothesis or theory that predicts the relationship between two variables - the independent (predictor) and the dependent (predicted). 

Complex hypothesis

The term complex hypothesis refers to a model – either quantitative (mathematical) or qualitative . A complex hypothesis states the surmised relationship between two or more potentially related variables.

Directional hypothesis

When creating a statistical hypothesis, the directional hypothesis (the null hypothesis) states an assumption regarding one parameter of a population. Some academics call this the “one-sided” hypothesis. The alternative hypothesis indicates whether the researcher tests for a positive or negative effect by including either the greater than (">") or less than ("<") sign.

Non-directional hypothesis

We refer to the alternative hypothesis in a statistical research question as a non-directional hypothesis. It includes the not equal ("≠") sign to show that the research tests whether or not an effect exists without specifying the effect's direction (positive or negative).

Associative hypothesis

The term associative hypothesis assumes a link between two variables but stops short of stating that one variable impacts the other. Academic statistical literature asserts in this sense that correlation does not imply causation. So, although the hypothesis notes the correlation between two variables – the independent and dependent - it does not predict how the two interact.

Logical hypothesis

Typically used in philosophy rather than science, researchers can't test a logical hypothesis because the technology or data set doesn't yet exist. A logical hypothesis uses logic as the basis of its assumptions. 

In some cases, a logical hypothesis can become an empirical hypothesis once technology provides an opportunity for testing. Until that time, the question remains too expensive or complex to address. Note that a logical hypothesis is not a statistical hypothesis.

Empirical hypothesis

When we consider the opposite of a logical hypothesis, we call this an empirical or working hypothesis. This type of hypothesis considers a scientifically measurable question. A researcher can consider and test an empirical hypothesis through replicable tests, observations, and measurements.

Statistical hypothesis

The term statistical hypothesis refers to a test of a theory that uses representative statistical models to test relationships between variables to draw conclusions regarding a large population. This requires an existing large data set, commonly referred to as big data, or implementing a survey to obtain original statistical information to form a data set for the study. 

Testing this type of hypothesis requires the use of random samples. Note that the null and alternative hypotheses are used in statistical hypothesis testing.

Causal hypothesis

The term causal hypothesis refers to a research hypothesis that tests a cause-and-effect relationship. A causal hypothesis is utilized when conducting experimental or quasi-experimental research.

Descriptive hypothesis

The term descriptive hypothesis refers to a research hypothesis used in non-experimental research, specifying an influence in the relationship between two variables.

• What makes an effective research hypothesis?

An effective research hypothesis offers a clearly defined, specific statement, using simple wording that contains no assumptions or generalizations, and that you can test. A well-written hypothesis should predict the tested relationship and its outcome. It contains zero ambiguity and offers results you can observe and test. 

The research hypothesis should address a question relevant to a research area. Overall, your research hypothesis needs the following essentials:

Hypothesis Essential #1: Specificity & Clarity

Hypothesis Essential #2: Testability (Provability)

• How to develop a good research hypothesis

In developing your hypothesis statements, you must pre-plan some of your statistical analysis. Once you decide on your problem to examine, determine three aspects:

the parameter you'll test

the test's direction (left-tailed, right-tailed, or non-directional)

the hypothesized parameter value

Any quantitative research includes a hypothesized parameter value of a mean, a proportion, or the difference between two proportions. Here's how to note each parameter:

Single mean (μ)

Paired means (μd)

Single proportion (p)

Difference between two independent means (μ1−μ2)

Difference between two proportions (p1−p2)

Simple linear regression slope (β)

Correlation (ρ)

Defining these parameters and determining whether you want to test the mean, proportion, or differences helps you determine the statistical tests you'll conduct to analyze your data. When writing your hypothesis, you only need to decide which parameter to test and in what overarching way.

The null research hypothesis must include everyday language, in a single sentence, stating the problem you want to solve. Write it as an if-then statement with defined variables. Write an alternative research hypothesis that states the opposite.

• What is the correct format for writing a hypothesis?

The following example shows the proper format and textual content of a hypothesis. It follows commonly accepted academic standards.

Null hypothesis (H0): High school students who participate in varsity sports as opposed to those who do not, fail to score higher on leadership tests than students who do not participate.

Alternative hypothesis (H1): High school students who play a varsity sport as opposed to those who do not participate in team athletics will score higher on leadership tests than students who do not participate in athletics.

The research question tests the correlation between varsity sports participation and leadership qualities expressed as a score on leadership tests. It compares the population of athletes to non-athletes.

• What are the five steps of a hypothesis?

Once you decide on the specific problem or question you want to address, you can write your research hypothesis. Use this five-step system to hone your null hypothesis and generate your alternative hypothesis.

Step 1 : Create your research question. This topic should interest and excite you; answering it provides relevant information to an industry or academic area.

Step 2 : Conduct a literature review to gather essential existing research.

Step 3 : Write a clear, strong, simply worded sentence that explains your test parameter, test direction, and hypothesized parameter.

Step 4 : Read it a few times. Have others read it and ask them what they think it means. Refine your statement accordingly until it becomes understandable to everyone. While not everyone can or will comprehend every research study conducted, any person from the general population should be able to read your hypothesis and alternative hypothesis and understand the essential question you want to answer.

Step 5 : Re-write your null hypothesis until it reads simply and understandably. Write your alternative hypothesis.

What is the Red Queen hypothesis?

Some hypotheses are well-known, such as the Red Queen hypothesis. Choose your wording carefully, since you could become like the famed scientist Dr. Leigh Van Valen. In 1973, Dr. Van Valen proposed the Red Queen hypothesis to describe coevolutionary activity, specifically reciprocal evolutionary effects between species to explain extinction rates in the fossil record. 

Essentially, Van Valen theorized that to survive, each species remains in a constant state of adaptation, evolution, and proliferation, and constantly competes for survival alongside other species doing the same. Only by doing this can a species avoid extinction. Van Valen took the hypothesis title from the Lewis Carroll book, "Through the Looking Glass," which contains a key character named the Red Queen who explains to Alice that for all of her running, she's merely running in place.

• Getting started with your research

In conclusion, once you write your null hypothesis (H0) and an alternative hypothesis (Ha), you’ve essentially authored the elevator pitch of your research. These two one-sentence statements describe your topic in simple, understandable terms that both professionals and laymen can understand. They provide the starting point of your research project.

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How to Write a Hypothesis – Steps & Tips

Published by Alaxendra Bets at August 14th, 2021 , Revised On October 26, 2023

What is a Research Hypothesis?

You can test a research statement with the help of experimental or theoretical research, known as a hypothesis.

If you want to find out the similarities, differences, and relationships between variables, you must write a testable hypothesis before compiling the data, performing analysis, and generating results to complete.

The data analysis and findings will help you test the hypothesis and see whether it is true or false. Here is all you need to know about how to write a hypothesis for a  dissertation .

Research Hypothesis Definition

Not sure what the meaning of the research hypothesis is?

A research hypothesis predicts an answer to the research question  based on existing theoretical knowledge or experimental data.

Some studies may have multiple hypothesis statements depending on the research question(s).  A research hypothesis must be based on formulas, facts, and theories. It should be testable by data analysis, observations, experiments, or other scientific methodologies that can refute or support the statement.

Variables in Hypothesis

Developing a hypothesis is easy. Most research studies have two or more variables in the hypothesis, particularly studies involving correlational and experimental research. The researcher can control or change the independent variable(s) while measuring and observing the independent variable(s).

“How long a student sleeps affects test scores.”

In the above statement, the dependent variable is the test score, while the independent variable is the length of time spent in sleep. Developing a hypothesis will be easy if you know your research’s dependent and independent variables.

Once you have developed a thesis statement, questions such as how to write a hypothesis for the dissertation and how to test a research hypothesis become pretty straightforward.

Looking for dissertation help?

Researchprospect to the rescue then.

We have expert writers on our team who are skilled at helping students with quantitative dissertations across a variety of STEM disciplines. Guaranteeing 100% satisfaction!

Step-by-Step Guide on How to Write a Hypothesis

Here are the steps involved in how to write a hypothesis for a dissertation.

Step 1: Start with a Research Question

• Begin by asking a specific question about a topic of interest.
• This question should be clear, concise, and researchable.

Example: Does exposure to sunlight affect plant growth?

Step 2: Do Preliminary Research

• Before formulating a hypothesis, conduct background research to understand existing knowledge on the topic.
• Familiarise yourself with prior studies, theories, or observations related to the research question.

Step 3: Define Variables

• Independent Variable (IV): The factor that you change or manipulate in an experiment.
• Dependent Variable (DV): The factor that you measure.

Example: IV: Amount of sunlight exposure (e.g., 2 hours/day, 4 hours/day, 8 hours/day) DV: Plant growth (e.g., height in centimetres)

Step 4: Formulate the Hypothesis

• A hypothesis is a statement that predicts the relationship between variables.
• It is often written as an “if-then” statement.

Example: If plants receive more sunlight, then they will grow taller.

Step 5: Ensure it is Testable

A good hypothesis is empirically testable. This means you should be able to design an experiment or observation to test its validity.

Example: You can set up an experiment where plants are exposed to varying amounts of sunlight and then measure their growth over a period of time.

Step 6: Consider Potential Confounding Variables

• Confounding variables are factors other than the independent variable that might affect the outcome.
• It is important to identify these to ensure that they do not skew your results.

Example: Soil quality, water frequency, or type of plant can all affect growth. Consider keeping these constant in your experiment.

Step 7: Write the Null Hypothesis

• The null hypothesis is a statement that there is no effect or no relationship between the variables.
• It is what you aim to disprove or reject through your research.

Example: There is no difference in plant growth regardless of the amount of sunlight exposure.

Step 8: Test your Hypothesis

Design an experiment or conduct observations to test your hypothesis.

Example: Grow three sets of plants: one set exposed to 2 hours of sunlight daily, another exposed to 4 hours, and a third exposed to 8 hours. Measure and compare their growth after a set period.

Step 9: Analyse the Results

After testing, review your data to determine if it supports your hypothesis.

Step 10: Draw Conclusions

• Based on your findings, determine whether you can accept or reject the hypothesis.
• Remember, even if you reject your hypothesis, it’s a valuable result. It can guide future research and refine questions.

Three Ways to Phrase a Hypothesis

Try to use “if”… and “then”… to identify the variables. The independent variable should be present in the first part of the hypothesis, while the dependent variable will form the second part of the statement. Consider understanding the below research hypothesis example to create a specific, clear, and concise research hypothesis;

If an obese lady starts attending Zomba fitness classes, her health will improve.

In academic research, you can write the predicted variable relationship directly because most research studies correlate terms.

The number of Zomba fitness classes attended by the obese lady has a positive effect on health.

If your research compares two groups, then you can develop a hypothesis statement on their differences.

An obese lady who attended most Zumba fitness classes will have better health than those who attended a few.

How to Write a Null Hypothesis

If a statistical analysis is involved in your research, then you must create a null hypothesis. If you find any relationship between the variables, then the null hypothesis will be the default position that there is no relationship between them. H0 is the symbol for the null hypothesis, while the hypothesis is represented as H1. The null hypothesis will also answer your question, “How to test the research hypothesis in the dissertation.”

H0: The number of Zumba fitness classes attended by the obese lady does not affect her health.

H1: The number of Zumba fitness classes attended by obese lady positively affects health.

Also see:  Your Dissertation in Education

Hypothesis Examples

Research Question: Does the amount of sunlight a plant receives affect its growth? Hypothesis: Plants that receive more sunlight will grow taller than plants that receive less sunlight.

Research Question: Do students who eat breakfast perform better in school exams than those who don’t? Hypothesis: Students who eat a morning breakfast will score higher on school exams compared to students who skip breakfast.

Research Question: Does listening to music while studying impact a student’s ability to retain information? Hypothesis 1 (Directional): Students who listen to music while studying will retain less information than those who study in silence. Hypothesis 2 (Non-directional): There will be a difference in information retention between students who listen to music while studying and those who study in silence.

How can ResearchProspect Help?

If you are unsure about how to rest a research hypothesis in a dissertation or simply unsure about how to develop a hypothesis for your research, then you can take advantage of our dissertation services which cover every tiny aspect of a dissertation project you might need help with including but not limited to setting up a hypothesis and research questions,  help with individual chapters ,  full dissertation writing ,  statistical analysis , and much more.

Frequently Asked Questions

What are the 5 rules for writing a good hypothesis.

• Clear Statement: State a clear relationship between variables.
• Testable: Ensure it can be investigated and measured.
• Specific: Avoid vague terms, be precise in predictions.
• Falsifiable: Design to allow potential disproof.
• Relevant: Address research question and align with existing knowledge.

What is a hypothesis in simple words?

A hypothesis is an educated guess or prediction about something that can be tested. It is a statement that suggests a possible explanation for an event or phenomenon based on prior knowledge or observation. Scientists use hypotheses as a starting point for experiments to discover if they are true or false.

What is the hypothesis and examples?

A hypothesis is a testable prediction or explanation for an observation or phenomenon. For example, if plants are given sunlight, then they will grow. In this case, the hypothesis suggests that sunlight has a positive effect on plant growth. It can be tested by experimenting with plants in varying light conditions.

What is the hypothesis in research definition?

A hypothesis in research is a clear, testable statement predicting the possible outcome of a study based on prior knowledge and observation. It serves as the foundation for conducting experiments or investigations. Researchers test the validity of the hypothesis to draw conclusions and advance knowledge in a particular field.

Why is it called a hypothesis?

The term “hypothesis” originates from the Greek word “hypothesis,” which means “base” or “foundation.” It’s used to describe a foundational statement or proposition that can be tested. In scientific contexts, it denotes a tentative explanation for a phenomenon, serving as a starting point for investigation or experimentation.

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• How It Works

How to Write a Hypothesis

If I [do something], then [this] will happen.

This basic statement/formula should be pretty familiar to all of you as it is the starting point of almost every scientific project or paper. It is a hypothesis – a statement that showcases what you “think” will happen during an experiment. This assumption is made based on the knowledge, facts, and data you already have.

How do you write a hypothesis? If you have a clear understanding of the proper structure of a hypothesis, you should not find it too hard to create one. However, if you have never written a hypothesis before, you might find it a bit frustrating. In this article from EssayPro - custom essay writing services , we are going to tell you everything you need to know about hypotheses, their types, and practical tips for writing them.

Hypothesis Definition

According to the definition, a hypothesis is an assumption one makes based on existing knowledge. To elaborate, it is a statement that translates the initial research question into a logical prediction shaped on the basis of available facts and evidence. To solve a specific problem, one first needs to identify the research problem (research question), conduct initial research, and set out to answer the given question by performing experiments and observing their outcomes. However, before one can move to the experimental part of the research, they should first identify what they expect to see for results. At this stage, a scientist makes an educated guess and writes a hypothesis that he or she is going to prove or refute in the course of their study.

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A hypothesis can also be seen as a form of development of knowledge. It is a well-grounded assumption put forward to clarify the properties and causes of the phenomena being studied.

As a rule, a hypothesis is formed based on a number of observations and examples that confirm it. This way, it looks plausible as it is backed up with some known information. The hypothesis is subsequently proved by turning it into an established fact or refuted (for example, by pointing out a counterexample), which allows it to attribute it to the category of false statements.

As a student, you may be asked to create a hypothesis statement as a part of your academic papers. Hypothesis-based approaches are commonly used among scientific academic works, including but not limited to research papers, theses, and dissertations.

Note that in some disciplines, a hypothesis statement is called a thesis statement. However, its essence and purpose remain unchanged – this statement aims to make an assumption regarding the outcomes of the investigation that will either be proved or refuted.

Characteristics and Sources of a Hypothesis

Now, as you know what a hypothesis is in a nutshell, let’s look at the key characteristics that define it:

• It has to be clear and accurate in order to look reliable.
• It has to be specific.
• There should be scope for further investigation and experiments.
• A hypothesis should be explained in simple language—while retaining its significance.
• If you are making a relational hypothesis, two essential elements you have to include are variables and the relationship between them.

The main sources of a hypothesis are:

• Scientific theories.
• Observations from previous studies and current experiences.
• The resemblance among different phenomena.
• General patterns that affect people’s thinking process.

Types of Hypothesis

Basically, there are two major types of scientific hypothesis: alternative and null.

• Alternative Hypothesis

This type of hypothesis is generally denoted as H1. This statement is used to identify the expected outcome of your research. According to the alternative hypothesis definition, this type of hypothesis can be further divided into two subcategories:

• Directional — a statement that explains the direction of the expected outcomes. Sometimes this type of hypothesis is used to study the relationship between variables rather than comparing between the groups.
• Non-directional — unlike the directional alternative hypothesis, a non-directional one does not imply a specific direction of the expected outcomes.

Now, let’s see an alternative hypothesis example for each type:

Directional: Attending more lectures will result in improved test scores among students. Non-directional: Lecture attendance will influence test scores among students.

Notice how in the directional hypothesis we specified that the attendance of more lectures will boost student’s performance on tests, whereas in the non-directional hypothesis we only stated that there is a relationship between the two variables (i.e. lecture attendance and students’ test scores) but did not specify whether the performance will improve or decrease.

• Null Hypothesis

This type of hypothesis is generally denoted as H0. This statement is the complete opposite of what you expect or predict will happen throughout the course of your study—meaning it is the opposite of your alternative hypothesis. Simply put, a null hypothesis claims that there is no exact or actual correlation between the variables defined in the hypothesis.

To give you a better idea of how to write a null hypothesis, here is a clear example: Lecture attendance has no effect on student’s test scores.

Both of these types of hypotheses provide specific clarifications and restatements of the research problem. The main difference between these hypotheses and a research problem is that the latter is just a question that can’t be tested, whereas hypotheses can.

Based on the alternative and null hypothesis examples provided earlier, we can conclude that the importance and main purpose of these hypotheses are that they deliver a rough description of the subject matter. The main purpose of these statements is to give an investigator a specific guess that can be directly tested in a study. Simply put, a hypothesis outlines the framework, scope, and direction for the study. Although null and alternative hypotheses are the major types, there are also a few more to keep in mind:

Research Hypothesis — a statement that is used to test the correlation between two or more variables.

For example: Eating vitamin-rich foods affects human health.

Simple Hypothesis — a statement used to indicate the correlation between one independent and one dependent variable.

For example: Eating more vegetables leads to better immunity.

Complex Hypothesis — a statement used to indicate the correlation between two or more independent variables and two or more dependent variables.

For example: Eating more fruits and vegetables leads to better immunity, weight loss, and lower risk of diseases.

Associative and Causal Hypothesis — an associative hypothesis is a statement used to indicate the correlation between variables under the scenario when a change in one variable inevitably changes the other variable. A causal hypothesis is a statement that highlights the cause and effect relationship between variables.

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Hypothesis vs Prediction

When speaking of hypotheses, another term that comes to mind is prediction. These two terms are often used interchangeably, which can be rather confusing. Although both a hypothesis and prediction can generally be defined as “guesses” and can be easy to confuse, these terms are different. The main difference between a hypothesis and a prediction is that the first is predominantly used in science, while the latter is most often used outside of science.

Simply put, a hypothesis is an intelligent assumption. It is a guess made regarding the nature of the unknown (or less known) phenomena based on existing knowledge, studies, and/or series of experiments, and is otherwise grounded by valid facts. The main purpose of a hypothesis is to use available facts to create a logical relationship between variables in order to provide a more precise scientific explanation. Additionally, hypotheses are statements that can be tested with further experiments. It is an assumption you make regarding the flow and outcome(s) of your research study.

A prediction, on the contrary, is a guess that often lacks grounding. Although, in theory, a prediction can be scientific, in most cases it is rather fictional—i.e. a pure guess that is not based on current knowledge and/or facts. As a rule, predictions are linked to foretelling events that may or may not occur in the future. Often, a person who makes predictions has little or no actual knowledge of the subject matter he or she makes the assumption about.

Another big difference between these terms is in the methodology used to prove each of them. A prediction can only be proven once. You can determine whether it is right or wrong only upon the occurrence or non-occurrence of the predicted event. A hypothesis, on the other hand, offers scope for further testing and experiments. Additionally, a hypothesis can be proven in multiple stages. This basically means that a single hypothesis can be proven or refuted numerous times by different scientists who use different scientific tools and methods.

To give you a better idea of how a hypothesis is different from a prediction, let’s look at the following examples:

Hypothesis: If I eat more vegetables and fruits, then I will lose weight faster.

This is a hypothesis because it is based on generally available knowledge (i.e. fruits and vegetables include fewer calories compared to other foods) and past experiences (i.e. people who give preference to healthier foods like fruits and vegetables are losing weight easier). It is still a guess, but it is based on facts and can be tested with an experiment.

Prediction: The end of the world will occur in 2023.

This is a prediction because it foretells future events. However, this assumption is fictional as it doesn’t have any actual grounded evidence supported by facts.

Based on everything that was said earlier and our examples, we can highlight the following key takeaways:

• A hypothesis, unlike a prediction, is a more intelligent assumption based on facts.
• Hypotheses define existing variables and analyze the relationship(s) between them.
• Predictions are most often fictional and lack grounding.
• A prediction is most often used to foretell events in the future.
• A prediction can only be proven once – when the predicted event occurs or doesn’t occur. 
• A hypothesis can remain a hypothesis even if one scientist has already proven or disproven it. Other scientists in the future can obtain a different result using other methods and tools.

We also recommend that you read about some informative essay topics .

Now, as you know what a hypothesis is, what types of it exist, and how it differs from a prediction, you are probably wondering how to state a hypothesis. In this section, we will guide you through the main stages of writing a good hypothesis and provide handy tips and examples to help you overcome this challenge:

1. Define Your Research Question

Here is one thing to keep in mind – regardless of the paper or project you are working on, the process should always start with asking the right research question. A perfect research question should be specific, clear, focused (meaning not too broad), and manageable.

Example: How does eating fruits and vegetables affect human health?

2. Conduct Your Basic Initial Research

As you already know, a hypothesis is an educated guess of the expected results and outcomes of an investigation. Thus, it is vital to collect some information before you can make this assumption.

At this stage, you should find an answer to your research question based on what has already been discovered. Search for facts, past studies, theories, etc. Based on the collected information, you should be able to make a logical and intelligent guess.

3. Formulate a Hypothesis

Based on the initial research, you should have a certain idea of what you may find throughout the course of your research. Use this knowledge to shape a clear and concise hypothesis.

Based on the type of project you are working on, and the type of hypothesis you are planning to use, you can restate your hypothesis in several different ways:

Non-directional: Eating fruits and vegetables will affect one’s human physical health. Directional: Eating fruits and vegetables will positively affect one’s human physical health. Null: Eating fruits and vegetables will have no effect on one’s human physical health.

4. Refine Your Hypothesis

Finally, the last stage of creating a good hypothesis is refining what you’ve got. During this step, you need to define whether your hypothesis:

• Has clear and relevant variables;
• Identifies the relationship between its variables;
• Is specific and testable;
• Suggests a predicted result of the investigation or experiment.

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Hypothesis Examples

Following a step-by-step guide and tips from our essay writers for hire , you should be able to create good hypotheses with ease. To give you a starting point, we have also compiled a list of different research questions with one hypothesis and one null hypothesis example for each:

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Sometimes, coping with a large academic load is just too much for a student to handle. Papers like research papers and dissertations can take too much time and effort to write, and, often, a hypothesis is a necessary starting point to get the task on track. Writing or editing a hypothesis is not as easy as it may seem. However, if you need help with forming it, the team at EssayPro is always ready to come to your rescue! If you’re feeling stuck, or don’t have enough time to cope with other tasks, don’t hesitate to send us you rewrite my essay for me or any other request.

is an expert in nursing and healthcare, with a strong background in history, law, and literature. Holding advanced degrees in nursing and public health, his analytical approach and comprehensive knowledge help students navigate complex topics. On EssayPro blog, Adam provides insightful articles on everything from historical analysis to the intricacies of healthcare policies. In his downtime, he enjoys historical documentaries and volunteering at local clinics.

How To Write A Research Paper

How To Write A Hypothesis

How To Write a Hypothesis in a Research Paper | Steps & Examples

13 min read

Published on: Aug 5, 2021

Last updated on: Mar 5, 2024

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Imagine spending hours conducting experiments, only to realize that your hypothesis is unclear or poorly constructed.

This can lead to wasted time, resources, and a lack of meaningful results.

Fortunately, by mastering the art of hypothesis writing, you can ensure that your research paper is focused and structured. 

This comprehensive guide will provide you with step-by-step instructions and examples to write a hypothesis effectively.

By the end of this guide, you will have all the knowledge to write hypotheses that drive impactful scientific research.

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What is a Hypothesis?

A hypothesis is a tentative explanation or prediction that can be tested through scientific investigation. 

It is like a roadmap that guides researchers in their quest for answers. By formulating a hypothesis, researchers make educated guesses about the relationship between variables or phenomena.

Think of a hypothesis as a detective's hunch. Just like a detective forms a theory about a crime based on evidence, a researcher develops a hypothesis based on existing knowledge and observations. 

Now that we have a basic understanding of what a hypothesis is, let's delve into the process of writing one effectively.

Variables in Hypothesis

In hypotheses, variables play a crucial role as they represent the factors that are being studied and tested. 

Let's explore two types of variables commonly found in hypotheses:

1. Independent Variable: This variable is manipulated or controlled by the researcher. It is the factor believed to have an effect on the dependent variable. Here's an example:

Hypothesis: "Increasing study time (independent variable) leads to improved test scores (dependent variable) in students."

In this hypothesis, the independent variable is the study time, which the researcher can manipulate to observe its impact on the test scores.

2. Dependent Variable: This variable is the outcome or response that is measured or observed as a result of the changes in the independent variable. Here's an example:

Hypothesis: "Exposure to sunlight (independent variable) affects plant growth (dependent variable)."

In this hypothesis, the dependent variable is plant growth, which is expected to be influenced by the independent variable, sunlight exposure. The researcher measures or observes the changes in plant growth based on the different levels of sunlight exposure.

Research Question vs Hypothesis

A research question is an inquiry that defines the focus and direction of a research study. A hypothesis, on the other hand, is a tentative statement that suggests a relationship between variables or predicts the outcome of a research study.

Hypothesis vs. Prediction

The difference between a hypothesis and a prediction is slight, but it's critical to understand. 

Hypotheses are a great way to explain why something happens based on scientific methods. A prediction is a statement that says something will happen based on what has been observed.

A hypothesis is a statement with variables. A prediction is a statement that says what will happen in the future.

Theory vs. Hypothesis

The theory and hypothesis have some differences between them.

• A hypothesis is the explanation of a phenomenon that will be supported through scientific methods. 
• A theory is a well-substantiated and already-tested explanation backed by evidence.  

To turn a hypothesis into a theory, you need to test it in different situations and with strong evidence. Theories can also be used to make predictions about something that is not understood. Once you have predictions, you can turn them into hypotheses that can be tested.

How to Develop a Hypothesis Step by Step?

Developing a hypothesis is an important step in scientific research, as it sets the foundation for designing experiments and testing theories. 

Let's explore the step-by-step process of developing a hypothesis, using the example of studying the effects of exercise on sleep quality.

Step 1. Ask a Question

To begin, ask a specific question that focuses on the relationship between variables. In our example, the question could be: "Does regular exercise have a positive impact on sleep quality?"

Step 2. Do Background Research

Before formulating your hypothesis, conduct preliminary research to gather existing knowledge on the topic. 

Review scientific studies, articles, and relevant literature to understand the current understanding of exercise and its potential effects on sleep quality. This research will provide a foundation for formulating your hypothesis.

Step 3. Develop Your Hypothesis

Based on your question and preliminary research, formulate a hypothesis that predicts the expected relationship between variables. In our example, the hypothesis could be: 

"Regular exercise has a positive influence on sleep quality, resulting in improved sleep duration and reduced sleep disturbances."

Step 4. Refine Your Hypothesis

Refine your hypothesis by making it more specific and testable. Specify the variables involved and the anticipated outcomes in clear terms. For instance: 

"Engaging in moderate-intensity aerobic exercise for at least 30 minutes, three times a week, will lead to an increase in total sleep time and a decrease in the frequency of sleep disruptions."

Step 5. Express Your Hypothesis in Three Forms

To ensure comprehensiveness, phrase your hypothesis in three different ways: as a simple statement, as a positive correlation, and as a negative correlation. This will cover different perspectives and potential outcomes. 

Using our example:

• Simple Statement: "Regular exercise positively affects sleep quality."
• Positive Correlation: "As the frequency of regular exercise increases, sleep quality improves."
• Negative Correlation: "A lack of regular exercise is associated with poorer sleep quality."

Step 6. Construct a Null Hypothesis

In addition to the main hypothesis, it is important to write a null hypothesis. The null hypothesis assumes that there is no significant relationship between the variables being studied. 

The example below shows how to state the null hypothesis in a research paper: 

By following these steps, you can develop a well-structured and testable hypothesis that serves as a guiding framework for your scientific research.

Types of Research Hypotheses with Examples

Hypotheses come in various forms, depending on the nature of the research and the relationship between variables. 

Here are seven common types of hypotheses along with examples:

• Simple Hypothesis: A straightforward statement about the expected relationship between variables.

Example: "Increasing fertilizer dosage will lead to higher crop yields."

• Complex Hypothesis: A hypothesis that suggests a more intricate relationship between multiple variables.

Example: "The interaction of genetic factors and environmental stressors contributes to the development of certain mental disorders."

• Directional Hypothesis: A hypothesis that predicts the specific direction of the relationship between variables.

Example: "As temperature decreases, the viscosity of the liquid will increase."

• Non-Directional Hypothesis: A hypothesis that suggests a relationship between variables without specifying the direction.

Example: "There is a correlation between caffeine consumption and anxiety levels."

• Null Hypothesis: A hypothesis that assumes no significant relationship between variables.

Example: "There is no difference in exam performance between students who study in silence and students who listen to music."

• Alternative Hypothesis: A hypothesis that contradicts or offers an alternative explanation to the null hypothesis.

Example: "There is a significant difference in weight loss between individuals following a low-carb diet and those following a low-fat diet."

• Associative Hypothesis: A hypothesis that suggests a relationship between variables without implying causality.

Example: "There is a correlation between exercise frequency and cardiovascular health."

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What Makes a Good Hypothesis? 5 Key Elements

Crafting a good hypothesis is essential for conducting effective scientific research. A well-formed hypothesis sets the stage for meaningful experiments. 

Here are some key characteristics that make a hypothesis strong:

1. Testable and Specific

A good hypothesis should be testable through observation or experimentation. It should be formulated in a way that allows researchers to gather data and evidence to support or refute it. 

When writing a research hypothesis, it is crucial to structure it in a manner that suggests clear ways to measure or observe the variables involved.

2. Grounded in Existing Knowledge

A strong hypothesis is built upon a foundation of existing knowledge and understanding of the topic. By connecting your hypothesis to previous findings, you ensure that your research contributes to the broader scientific knowledge. 

This incorporation of existing knowledge aligns with the concept of research hypotheses, where hypotheses are framed based on the understanding of the subject from previous studies.

3. Falsifiable

A good hypothesis must be falsifiable, meaning that it can be proven false if it is indeed false. This principle is important because it allows for rigorous testing and prevents researchers from making claims that are impossible to verify or disprove. 

This aligns with the idea of statistical hypothesis, where hypotheses need to be formulated in a way that allows statistical testing to determine their validity.

4. Clearly Defines Variables

A well-formulated hypothesis clearly identifies the independent and dependent variables involved in the research. It specifies the relationship between two variables and states what researchers expect to find during the study. 

The clarity in defining variables is a crucial aspect of developing logical hypotheses.

5. Supported by Logic and Reasoning

A good hypothesis is logical and based on sound reasoning. It should be supported by evidence and a plausible rationale. The relationship between two variables proposed in the hypothesis should be grounded in a solid understanding of cause-and-effect relationships and theories.

A strong hypothesis, whether it is a research hypothesis, statistical hypothesis, or logical hypothesis, encompasses these key elements. By incorporating these elements you lay the groundwork for a robust and meaningful research study.

Hypothesis Examples 

Here are a few more examples for you to look at and get a better understanding!

How to Write a Hypothesis in Research

Research Question: "Does exposure to violent video games increase aggressive behavior in adolescents?"

Hypothesis 1: "Adolescents who are exposed to violent video games will display higher levels of aggressive behavior compared to those who are not exposed."

Hypothesis 2: "There is a positive correlation between the amount of time spent playing violent video games and the level of aggressive behavior exhibited by adolescents."

How to Write a Hypothesis for a Lab Report:

Lab Experiment: Testing the effect of different fertilizers on plant growth.

Hypothesis 1: "Plants treated with fertilizer A will exhibit greater growth in terms of height and leaf count compared to plants treated with fertilizer B."

Hypothesis 2: "There is a significant difference in the growth rate of plants when exposed to different types of fertilizers."

How to Write a Hypothesis in a Report:

Report Topic: Investigating the impact of social media usage on self-esteem.

Hypothesis 1: "Individuals who spend more time on social media will report lower levels of self-esteem compared to those who spend less time on social media."

Hypothesis 2: "There is an inverse relationship between the frequency of social media use and self-esteem levels among individuals."

Example of Hypothesis in a Research Proposal:

Crafting hypotheses in a research proposal is pivotal for outlining the research aims and guiding the investigative process. Here's an example of a hypothesis within a research proposal:

Research Proposal Topic: Investigating the impact of social media usage on adolescents' self-esteem levels.

Hypothesis: "Adolescents who spend more time on social media platforms will have lower self-esteem levels compared to those who spend less time on social media."

How To Write a Hypothesis Psychology

Research Topic: Investigating the impact of mindfulness meditation on reducing symptoms of anxiety in college students.

Hypothesis 1: "College students who regularly practice mindfulness meditation will report lower levels of anxiety compared to those who do not engage in mindfulness practices."

Hypothesis 2: "There will be a significant decrease in anxiety scores among college students who undergo a structured mindfulness meditation program compared to a control group receiving no intervention."

How to Write a Hypothesis for a Research Paper:

 Research Paper Topic: Examining the effect of mindfulness meditation on stress reduction.

Hypothesis 1: "Participating in regular mindfulness meditation practice will result in a significant decrease in perceived stress levels among participants."

Hypothesis 2: "There is a positive association between the frequency of mindfulness meditation practice and the reduction of stress levels in individuals."

How to Write a Hypothesis for Qualitative Research:

Qualitative Research Topic: Exploring the experiences of first-time mothers during the postpartum period.

Hypothesis 1: "First-time mothers will report feelings of increased anxiety and stress during the early weeks of the postpartum period."

Hypothesis 2: "There will be a common theme of adjustment challenges among first-time mothers in their narratives about the postpartum experience."

Good and Bad Hypothesis Example

Below are examples of good and bad hypotheses, along with their corresponding research question and hypothesis examples:

In conclusion, a well-crafted hypothesis sets the stage for designing experiments, collecting data, and drawing meaningful conclusions. 

By following the steps of formulating a hypothesis, researchers can ensure that their investigations are grounded in solid reasoning. AI essay writing tools can be a great help in getting ideas.

However, If you need assistance with essay writing, consider leveraging the services of CollegeEssay.org. Our team of experienced writers is dedicated to delivering high-quality, customized essays that meet your requirements and deadlines. 

Don't hesitate to visit CollegeEssay.org and benefit from our professional essay writing service . Contact us today and say goodbye to your academic paper-writing worries.

Frequently Asked Questions

What are the 3 required parts of a hypothesis.

The three main parts of the hypothesis are: 

• Problem 
• Proposed solution 
• Result 

What are 5 characteristics of a good hypothesis?

The main five characteristics of a good hypothesis are: 

• Clarity 
• Relevant to problem 
• Consistency 
• Specific 
• Testability 

What should not be characteristic of a hypothesis?

Complexity should not be a good characteristic of a hypothesis. 

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As a Digital Content Strategist, Nova Allison has eight years of experience in writing both technical and scientific content. With a focus on developing online content plans that engage audiences, Nova strives to write pieces that are not only informative but captivating as well.

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How to Write a Good Hypothesis in a Research Paper

What is a hypothesis in a research paper.

Every research has many parts, but its vital part is the proper hypothesis construction. A hypothesis represents a question, which includes an expected or predicted research result. When there’s no hypothesis, the base for an experiment or research is missing. With that said, it’s essential to carefully build the hypothesis. Such writing projects require patience, thoroughness, and persistence. Here, you’ll learn what is a hypothesis in research and how to write a hypothesis for a research paper and construct it clearly.

Characteristics of a Great Hypothesis

When you start learning how to write hypothesis, it’s crucial to understand what makes it good.

• It should be concise, precise, and clear
• It should be testable
• It should be focused on one problem only
• All great hypotheses aren’t contradictory
• It should be stated simply and clearly. That way, everyone can understand it with ease.

All this may sound too complex. At the start, everything seems complicated and confusing. But most beginnings are like that. Learning other things, including writing an  appendix for a research paper are tricky, but once you get into it, it becomes easier. Learning new things, especially of scientific nature, requires effort and patience.

Before you start working on hypotheses, there’re several questions every researcher should ask, including:

• Is the language used for the scientific reports clear?
• How can the thesis be tested? In what ways?
• Which explanations should be explored?
• Does the theory include different variables, dependent and independent?
• Is the idea in conflict with any nature laws?

Every question is equally important. These point to the complexity of the work. For many students, a scientific study is too complicated, more complex than learning how to write a  method section for a research paper or learning how to conclude a subject. But diving into it often turns into a fun journey.

Make sure to provide answers for all the above. If something is missing or doesn’t seem suitable, it means you’ll have to make appropriate changes.

General Types of the Research Hypothesis

There’re several general hypothesis types to explore, and those are:

• Simple — This type foresees the relation between a single independent variable and a dependent one.
• Complex — Focuses on foreseeing the connection between two or more independent variables and two or more dependent ones.
• Directional — It focuses on giving an explanation of the expected outcome direction.
• Non-directional — It doesn’t explain the expected direction of the result.
• Associative — It points out how the change in one of the variables affects the other.
• Causal — It shows how the manipulation of an independent variable affects the dependent one.
• Null — It points out there’s no relation between variables.
• Alternative — It shows the relationship between variables and identifies the expected research result.

Learning how to distinguish all these types takes time. With proper understanding, the entire study becomes easier. However, some students turn to professional help, and you can do the same — simply buy your research paper online because experienced researchers create them. These researchers possess the knowledge and skills to deliver exceptional work.

Keep in mind that one theory can fall into one of the types mentioned above or into several types. All the definitions previously listed are created to be simple and understandable for beginners.

Main Steps: How to Write the Hypothesis Section of a Research Paper

Here’re the footsteps on how to write a hypothesis in a research paper that you should follow:

• First, ask a  question , for example: “How does exercise affect sleep?”
• Start collecting data — take experiments, conduct interviews, and explore academic journals. Gather information from many sources and different sides.
• Create the answer to the previously asked question: “Exercise decreases insomnia, along with other sleep issues and complaints, and its effects are similar to results sleeping pills are providing.”
• Create the hypothesis — It should include variables, outcomes, and who or what is studied. “If a person regularly exercises, they will have better sleep quality and sleep complaints will reduce.”
• Clarify the hypothesis by exploring the difference or connection between the two groups.
• Null hypothesis creation — Finally, formulate a hypothesis — null (that points out there’s no evidence that supports differences) or alternative (showing proof there’re differences).

The process is complex and requires time, effort, and exploration. It’s tricky even for experienced people. That is why many students turn to  custom writing service where professionals provide all the work at affordable prices, following the format and other requirements of scientific research.

When you start working on your assignment, ensure to follow all the steps we’ve listed. That way, you’ll ensure nothing is missing.

How to Create a Strong Hypothesis for the Research Paper?

Creating a solid hypothesis requires several things, and those are:

• First, state the issue — the topic needs to be clearly defined.
• If possible, use the statement that has the If and Then components. In other words, if some specific action is taking place, then the particular result is anticipated.
• Variables need to be detected. In the example above, the variables are exercise and sleep.

Learning how to write a null hypothesis in a research paper isn’t easy. There’re many parts to understand, but carefully following a  guide to writing a research paper can be very helpful. Give yourself time and be patient until you figure it out.

As you may notice, there are a couple of crucial steps to follow. One of the key factors is to follow the guide and ensure that you are clear and concise.

Hypothesis Examples

Before you start working on study articles, here’re some hypothesis samples that’ll help you get a better understanding of how things work:

• Brushing the teeth every day prevents the formation of cavities.
• Eating broccoli and berries boosts the metabolism.
• Students that don’t skip breakfast perform better in school than those who do skip breakfast.
• When fertilizing the garden, the plants will grow more quicker.
• When taking adequate breaks, employees’ work performance increases.

When you don’t have enough time for a proper study and data collection, there’s an option to  pay for writing a research paper that many students use, even the top researchers. Everyone needs a break at times. Plus, these services are affordable and tailored to match the budget of a student.

We’ve created the examples above so every student that is new to this type of work can get familiar with the basics. At first glance, getting it all seems like a lot. But as you keep exploring the examples, things will get easier.

All researches require a lot of effort, especially when you are a beginner. Creating a hypothesis and developing an entire essay about a particular question isn’t always easy. You have a lot of analysis in front of you, some experiments, data collection, and more. Even though a tremendous amount of work is required, completing statistical analysis and the project altogether is pretty fun. Remember, if you are busy, professionals can do it for you.

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Where to Put the Research Question in a Paper

Silke Haidekker has a PhD in Pharmacology from the University of Hannover. She is a Clinical Research Associate in multiple pharmaceutical companies in Germany and the USA. She now works as a full-time medical translator and writer in a small town in Georgia.

Of Rats and Panic Attacks: A Doctoral Student’s Tale

You would probably agree that the time spent writing your PhD dissertation or thesis is not only a time of taking pride or even joy in what you do, but also a time riddled with panic attacks of different varieties and lengths. When I worked on my PhD thesis in pharmacology in Germany many years back, I had  my  first panic attack as I first learned how to kill rats for my experiments with a very ugly tool called a guillotine! After that part of the procedure, I was to remove and mash their livers, spike them with Ciclosporin A (an immunosuppressive agent), and then present the metabolites by high-pressure liquid chromatography.

Many rats later, I had another serious panic attack. It occurred at the moment my doctoral adviser told me to write my first research paper on the Ciclosporin A metabolites I had detected in hundreds of slimy mashes of rat liver. Sadly, this second panic attack led to a third one that was caused by living in the pre-internet era, when it was not as easy to access information about  how to write research papers .

How I got over writing my first research paper is now ancient history. But it was only years later, living in the USA and finally being immersed in the language of most scientific research papers, that my interest in the art of writing “good” research papers was sparked during conferences held by the  American Medical Writers Association , as well as by getting involved in different writing programs and academic self-study courses.

How to State the Research Question in the Introduction Section

Good writing begins with clearly stating your research question (or hypothesis) in the Introduction section —the focal point on which your entire paper builds and unfolds in the subsequent Methods, Results, and Discussion sections . This research question or hypothesis that goes into the first section of your research manuscript, the Introduction, explains at least three major elements:

a) What is  known  or believed about the research topic?

B) what is still  unknown  (or problematic), c) what is the  question or hypothesis  of your investigation.

Some medical writers refer to this organizational structure of the Introduction as a “funnel shape” because it starts broadly, with the bigger picture, and then follows one scientifically logical step after the other until finally narrowing down the story to the focal point of your research at the end of the funnel.

Let’s now look in greater detail at a research question example and how you can logically embed it into the Introduction to make it a powerful focal point and ignite the reader’s interest about the importance of your research:

a) The Known

You should start by giving your reader a brief overview of knowledge or previous studies already performed in the context of your research topic.

The topic of one of my research papers was “investigating the value of diabetes as an independent predictor of death in people with end-stage renal disease (ESRD).” So in the Introduction, I first presented the basic knowledge that diabetes is the leading cause of end-stage renal disease (ESRD) and thus made the reader better understand our interest in this specific study population. I then presented previous studies already showing that diabetes indeed seems to represent an independent risk factor for death in the general population. However, very few studies had been performed in the ESRD population and those only yielded controversial results.

Example :  “It seems well established that there is a link between diabetic nephropathy and hypertensive nephropathy and end-stage renal disease (ESRD) in Western countries. In 2014, 73% of patients in US hospitals had comorbid ESRD and type 2 diabetes (1, 2, 3)…”

b) The Unknown

In our example, this “controversy” flags the “unknown” or “problematic” and therefore provides strong reasons for why further research is justified. The unknown should be clearly stated or implied by using phrases such as “were controversial” (as in our example), “…has not been determined,” or “…is unclear.” By clearly stating what is “unknown,” you indicate that your research is new. This creates a smooth transition into your research question.

Example :  “However, previous studies have failed to isolate diabetes as an independent factor, and thus much remains unknown about specific risk factors associated with both diabetes and ESRD .”

c) The Research Question (Hypothesis)

Your research question is the question that inevitably evolves from the deficits or problems revealed in the “Unknown” and clearly states the goal of your research. It is important to describe your research question in just one or two short sentences, but very precisely and including all variables studied, if applicable. A transition should be used to mark the transition from the unknown to the research question using one word such as “therefore” or “accordingly,” or short phrases like “for this reason” or “considering this lack of crucial information.”

In our example, we stated the research question as follows:

Example :  “Therefore, the primary goal of our study was to perform a Kaplan-Meier survival study and to investigate, by means of the Cox proportional hazard model, the value of diabetes as an independent predictor of death in diabetic patients with ESRD.”

Note that the research question may include the  experimental approach  of the study used to answer the research question.

Another powerful way to introduce the research question is to  state the research question as a hypothesis  so that the reader can more easily anticipate the answer. In our case, the question could be put as follows:

Example :  “To test the hypothesis that diabetes is an independent predictor of death in people with ESRD, we performed a Kaplan-Survival study and investigated the value of diabetes by means of the Cox proportional hazard model.”

Note that this sentence leads with an introductory clause that indicates the hypothesis itself, transitioning well into a synopsis of the approach in the second half of the sentence.

The generic framework of the Introduction can be modified to include, for example,  two  research questions instead of just one. In such a case, both questions must follow inevitably from the previous statements, meaning that the background information leading to the second question cannot be omitted. Otherwise, the Introduction will get confusing, with the reader not knowing where that question comes from.

Begin with your research purpose in mind

To conclude, here is my simple but most important advice for you as a researcher preparing to write a scientific paper (or just the Introduction of a research paper) for the first time: Think your research question through precisely before trying to write it down; have in mind the reasons for exactly why you wanted to do this specific research, what exactly you wanted to find out, and how (by which methods) you did your investigation. If you have the answers to these questions in mind (or even better, create a comprehensive outline ) before starting the paper, the actual writing process will be a piece of cake and you will finish it “like a rat up a drainpipe”! And hopefully with no panic attacks.

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Before submitting your master’s thesis or PhD dissertation to academic journals for publication, be sure to receive proofreading services (including research paper editing , manuscript editing , thesis editing , and dissertation editing ) to ensure that your research writing is error-free. Impress your journal editor and get into the academic journal of your choice.    

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

What is a Hypothesis – Types, Examples and Writing Guide

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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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How to Develop a Research Topic

• Choose Your Topic
• Narrow Your Topic
• Formulate Your Research Question
• State Your Thesis or Hypothesis
• More Research Help

What is a thesis statement?

A  thesis statement  is a short, direct  sentence  that summarizes the main point or claim of an essay or research paper. If you have been asked to write a paper that supports a claim, you will probably need a thesis statement. The working thesis should summarize the answer to your main research question, and will likely change after you do some research.

A good thesis statement:

• tells the reader how you will interpret the significance of the subject matter under discussion.
• is a road map for the paper; in other words, it tells the reader what to expect from the rest of the paper.
• directly answers the question asked of you. A thesis is an interpretation of a question or subject, not the subject itself. The subject, or topic, of an essay might be World War II or Moby Dick; a thesis must then offer a way to understand the war or the novel.
• makes a claim that others might dispute.
• is usually a single sentence near the beginning of your paper (most often, at the end of the first paragraph) that presents your argument to the reader. The rest of the paper, the body of the essay, gathers and organizes evidence that will persuade the reader of the logic of your interpretation.

So, continuing to follow our example of active learning strategies and early chapter book readers, if we had decided to explore the question of "What is the relationship between the amount of time spent engaged in active learning activities associated with reading early chapter books and reading comprehension?" our thesis statement might be: Early chapter book readers who engage in active learning activities such as summarizing, story maps and think out loud demonstrate significant improvement on reading comprehension exams.

What is a hypothesis?

An  hypothesis  is a  statement  that can be proved or disproved. It is typically used  in  quantitative research and predicts the relationship  between  variables. 

A good hypothesis will be written as a statement or question that specifies:

• The dependent variable(s): who or what you expect to be affected
• The independent variable(s): who or what you predict will affect the dependent variable
• What you predict the effect will be.

If your assignment requires you to state an hypothesis, you will work with your professor to design a good hypothesis based on the standards of your field.

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HOW TO: Use Articles for Research: Introduction: Hypothesis/Thesis

• What's a Scholarly Journal?
• Reading the Citation
• Authors' Credentials
• Introduction: Hypothesis/Thesis
• Literature Review
• Research Method
• Results/Data
• Discussion/Conclusions

Hypothesis or Thesis

The first few paragraphs of a journal article serve to introduce the topic, to provide the author's hypothesis or thesis, and to indicate why the research was done.  A thesis or hypothesis is not always clearly labled; you may need to read through the introductory paragraphs to determine what the authors are proposing.

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• Research paper

Writing a Research Paper Introduction | Step-by-Step Guide

Published on September 24, 2022 by Jack Caulfield . Revised on September 5, 2024.

The introduction to a research paper is where you set up your topic and approach for the reader. It has several key goals:

• Present your topic and get the reader interested
• Provide background or summarize existing research
• Position your own approach
• Detail your specific research problem and problem statement
• Give an overview of the paper’s structure

The introduction looks slightly different depending on whether your paper presents the results of original empirical research or constructs an argument by engaging with a variety of sources.

The five steps in this article will help you put together an effective introduction for either type of research paper.

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Table of contents

Step 1: introduce your topic, step 2: describe the background, step 3: establish your research problem, step 4: specify your objective(s), step 5: map out your paper, research paper introduction examples, frequently asked questions about the research paper introduction.

The first job of the introduction is to tell the reader what your topic is and why it’s interesting or important. This is generally accomplished with a strong opening hook.

The hook is a striking opening sentence that clearly conveys the relevance of your topic. Think of an interesting fact or statistic, a strong statement, a question, or a brief anecdote that will get the reader wondering about your topic.

For example, the following could be an effective hook for an argumentative paper about the environmental impact of cattle farming:

A more empirical paper investigating the relationship of Instagram use with body image issues in adolescent girls might use the following hook:

Don’t feel that your hook necessarily has to be deeply impressive or creative. Clarity and relevance are still more important than catchiness. The key thing is to guide the reader into your topic and situate your ideas.

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This part of the introduction differs depending on what approach your paper is taking.

In a more argumentative paper, you’ll explore some general background here. In a more empirical paper, this is the place to review previous research and establish how yours fits in.

Argumentative paper: Background information

After you’ve caught your reader’s attention, specify a bit more, providing context and narrowing down your topic.

Provide only the most relevant background information. The introduction isn’t the place to get too in-depth; if more background is essential to your paper, it can appear in the body .

Empirical paper: Describing previous research

For a paper describing original research, you’ll instead provide an overview of the most relevant research that has already been conducted. This is a sort of miniature literature review —a sketch of the current state of research into your topic, boiled down to a few sentences.

This should be informed by genuine engagement with the literature. Your search can be less extensive than in a full literature review, but a clear sense of the relevant research is crucial to inform your own work.

Begin by establishing the kinds of research that have been done, and end with limitations or gaps in the research that you intend to respond to.

The next step is to clarify how your own research fits in and what problem it addresses.

Argumentative paper: Emphasize importance

In an argumentative research paper, you can simply state the problem you intend to discuss, and what is original or important about your argument.

Empirical paper: Relate to the literature

In an empirical research paper, try to lead into the problem on the basis of your discussion of the literature. Think in terms of these questions:

• What research gap is your work intended to fill?
• What limitations in previous work does it address?
• What contribution to knowledge does it make?

You can make the connection between your problem and the existing research using phrases like the following.

Now you’ll get into the specifics of what you intend to find out or express in your research paper.

The way you frame your research objectives varies. An argumentative paper presents a thesis statement, while an empirical paper generally poses a research question (sometimes with a hypothesis as to the answer).

Argumentative paper: Thesis statement

The thesis statement expresses the position that the rest of the paper will present evidence and arguments for. It can be presented in one or two sentences, and should state your position clearly and directly, without providing specific arguments for it at this point.

Empirical paper: Research question and hypothesis

The research question is the question you want to answer in an empirical research paper.

Present your research question clearly and directly, with a minimum of discussion at this point. The rest of the paper will be taken up with discussing and investigating this question; here you just need to express it.

A research question can be framed either directly or indirectly.

• This study set out to answer the following question: What effects does daily use of Instagram have on the prevalence of body image issues among adolescent girls?
• We investigated the effects of daily Instagram use on the prevalence of body image issues among adolescent girls.

If your research involved testing hypotheses , these should be stated along with your research question. They are usually presented in the past tense, since the hypothesis will already have been tested by the time you are writing up your paper.

For example, the following hypothesis might respond to the research question above:

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The final part of the introduction is often dedicated to a brief overview of the rest of the paper.

In a paper structured using the standard scientific “introduction, methods, results, discussion” format, this isn’t always necessary. But if your paper is structured in a less predictable way, it’s important to describe the shape of it for the reader.

If included, the overview should be concise, direct, and written in the present tense.

• This paper will first discuss several examples of survey-based research into adolescent social media use, then will go on to …
• This paper first discusses several examples of survey-based research into adolescent social media use, then goes on to …

Scribbr’s paraphrasing tool can help you rephrase sentences to give a clear overview of your arguments.

Full examples of research paper introductions are shown in the tabs below: one for an argumentative paper, the other for an empirical paper.

• Argumentative paper
• Empirical paper

Are cows responsible for climate change? A recent study (RIVM, 2019) shows that cattle farmers account for two thirds of agricultural nitrogen emissions in the Netherlands. These emissions result from nitrogen in manure, which can degrade into ammonia and enter the atmosphere. The study’s calculations show that agriculture is the main source of nitrogen pollution, accounting for 46% of the country’s total emissions. By comparison, road traffic and households are responsible for 6.1% each, the industrial sector for 1%. While efforts are being made to mitigate these emissions, policymakers are reluctant to reckon with the scale of the problem. The approach presented here is a radical one, but commensurate with the issue. This paper argues that the Dutch government must stimulate and subsidize livestock farmers, especially cattle farmers, to transition to sustainable vegetable farming. It first establishes the inadequacy of current mitigation measures, then discusses the various advantages of the results proposed, and finally addresses potential objections to the plan on economic grounds.

The rise of social media has been accompanied by a sharp increase in the prevalence of body image issues among women and girls. This correlation has received significant academic attention: Various empirical studies have been conducted into Facebook usage among adolescent girls (Tiggermann & Slater, 2013; Meier & Gray, 2014). These studies have consistently found that the visual and interactive aspects of the platform have the greatest influence on body image issues. Despite this, highly visual social media (HVSM) such as Instagram have yet to be robustly researched. This paper sets out to address this research gap. We investigated the effects of daily Instagram use on the prevalence of body image issues among adolescent girls. It was hypothesized that daily Instagram use would be associated with an increase in body image concerns and a decrease in self-esteem ratings.

The introduction of a research paper includes several key elements:

• A hook to catch the reader’s interest
• Relevant background on the topic
• Details of your research problem

and your problem statement

• A thesis statement or research question
• Sometimes an overview of the paper

Don’t feel that you have to write the introduction first. The introduction is often one of the last parts of the research paper you’ll write, along with the conclusion.

This is because it can be easier to introduce your paper once you’ve already written the body ; you may not have the clearest idea of your arguments until you’ve written them, and things can change during the writing process .

The way you present your research problem in your introduction varies depending on the nature of your research paper . A research paper that presents a sustained argument will usually encapsulate this argument in a thesis statement .

A research paper designed to present the results of empirical research tends to present a research question that it seeks to answer. It may also include a hypothesis —a prediction that will be confirmed or disproved by your research.

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Where to Find The Hypothesis in a Research Article

The question of “Where to Find The Hypothesis in a Research Article” can only be answered by exploring how research articles represent scientific methods.

Table of Contents

Introduction

A research article represents a compilation of information by a scientist concerning an original research idea. It is characterized by a wide range of information including, the purpose of the study, the thesis statement, hypothesis, literature review, methodology, results and conclusion.

The examination of a research article is an important process, and the ability to identify crucial elements of research is paramount for the effective analysis of a research article.

Research articles are usually arranged in specific ways. A hypothesis in a research article is usually located in a specific position in an article. The ability to quickly pinpoint where the hypothesis is located is crucial in becoming an expert in exploring research articles as well as formulating them.

What is a hypothesis

A hypothesis represents a scientific guess that is stated in research. It is a speculative statement concerning the relationship between two or more variables in research.

Therefore, a good hypothesis is a prediction that is testable, specific, and explores what a researcher expects to find in the study.

Formulating a Hypothesis

The creation of a hypothesis represents a critical part of the scientific method. Formulating a hypothesis is important, especially when testing a theory. Most scientific research involves testing theories. Theories, in this case, refer to ideas about the way things relate to one another. For one to formulate a hypothesis to be used in research, they have to be to predict the outcome of the research.

If one cannot predict the outcome, then the research does not need the formulating of a hypothesis because it is either exploratory or descriptive. These forms of research cannot have a hypothesis, and the reason is that there is a limited base of knowledge concerning the subject matter for the prediction of the outcome to be possible.

A good Hypothesis

A good hypothesis has to have two or more variables. These variables have to be measurable or have the potential to be measured. The hypothesis also has to specify how the variables are related to one another.

Where to Find the Hypothesis in a Research Article

The scientific method is characterized by several steps. They include:

• Coming up with a question or the problem that needs to be solved.
• Conducting background research on the problem
• Formulating a hypothesis
• Establishing how the research will be conducted using a research design
• Collecting data
• Analyzing the data and coming up with results
• Provide conclusions
• Presenting the information through a research article.

Based on the above structure, it is evident that the hypothesis is located in the introduction section of a research article. One should look out for “if-then” statements. However, for such statements to be hypotheses, they need to:

• Demonstrates the relationship between variables,
• The relationship needs to be testable and
• The prediction needs to be measurable

A hypothesis is not always clearly labeled. This means that the statement can appear in different forms apart from when formulated using the “if-then” statements. One should, therefore, look out for a statement that offers a prediction of what readers need to expect from the research.

The ability to identify where to find a hypothesis is located in a research article is very important in several ways:

• One can quickly know what the researcher wants to prove using the research.
• It makes individuals effective in reading research articles.
• It enhances an individual’s ability to formulate their own hypothesis when conducting research

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Hypothesis is a social annotation tool that can be embedded as an assignment directly into your CarmenCanvas course.

Watch the video below to see Hypothesis in action, or click here to jump to step-by-step instructions.

Step-by-step instructions

Upload your document.

Log into CarmenCanvas and select your course.

• Click on the  Files  tab on the left side of your screen
• Click on the gray  + Folder  button on the upper right corner of your screen
• Title the folder, “Hypothesis Documents”
• Select the  Hypothesis Documents folder
• Click on the scarlet  Upload  button in the upper right corner of your screen
• Select your document from your computer

Your document should now appear in your Hypothesis Documents folder.

Make a copy of the Hypothesis assignment template

Assignments in CarmenCanvas cannot be duplicated. You will need to copy the contents of the template and paste them into a new assignment.

Copy the template

• Click on the  Assignments  tab on the left side of your screen
• Select the  Hypothesis Reading Assignment Template
• Click on the  Edit Assignment Settings  button
• Select all of the content in the editor
• Right click and select  Copy

Paste template into new assignment

• Click on the scarlet  + Assignment  button on the upper right corner of your screen
• Title your assignment in the text entry field under  Assignment Name
• Right click inside of the editor and select  Paste
• Scroll down to the lower right corner of your screen and click on the scarlet  Save  button

Now you are ready to fill in the details of your assignment into the template. Use the template text as a guide and remove or edit content as needed.  

Add your document to the new assignment

• Scroll down to view the assignment settings and locate the  Submission Type  menu
• Click on the  Submission Type  dropdown menu and select the  External Tool  option
• Under External Tool Options, click on the gray  Find  button
• Scroll down if needed and select  Hypothesis
• If prompted, click on the  Authorize  button to allow Hypothesis to access your document
• Scroll through your Canvas files until you locate your document.
• You will know your document is selected when it turns a dark gray color
• Click on the dark gray  Select  button
• If your entire class will be annotating the document, click on the dark gray  Continue  button
• Scroll down and click  Save

The “Load Tool In New Tab” button will take you to the document in Hypothesis.

Dividing the assignment into groups

It is recommended that a maximum of 8 students engage in a Hypothesis assignment. If your class size is larger than 8 students, divide the hypothesis assignment into groups of 4-8 students by following the steps below.

• Toggle on the  This is a group assignment  button
• Toggle down the  Group set  dropdown and select the group set you will use for this assignment
• Click  Continue
• You will be taken back to the list where you had previously selected the Hypothesis tool
• Click the red  Select  button again to save your selections
• Toggle on the  Load This Tool In A New Tab  button

Watch an Ohio State instructor going through these steps.

Study of the one-dimensional consolidation and creep of clays with different thicknesses using different hypotheses and three elastic visco-plastic models

• Research Paper
• Open access
• Published: 25 September 2024

Cite this article

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• Ze-jian Chen   ORCID: orcid.org/0000-0001-7855-6234 1 ,
• Peng-lin Li   ORCID: orcid.org/0000-0003-4440-8457 1 ,
• Pei-chen Wu   ORCID: orcid.org/0000-0001-7900-3703 1 , 2 ,
• Jian-hua Yin   ORCID: orcid.org/0000-0002-7200-3695 1 , 2 &
• Ding-bao Song   ORCID: orcid.org/0000-0002-7840-9274 1  

The one-dimensional consolidation analysis of clays considering creep compression is a classical issue in soil mechanics and geotechnical design. The major debate lies in how to predict the consolidation settlement for a thick layer in the field using parameters obtained from a thin specimen from the laboratory. Different hypotheses have been advocated, based on which various methods and constitutive models have been developed. However, there are still some questions unaddressed and concepts inconsistently used, which may mislead engineers in the selection of methods/models and may result in settlements underestimated on a risk design side. In this paper, a state-of-the-art review and a thorough comparison study are performed on the existing methods and models for the consolidation analysis of clays exhibiting creep, from theoretical derivations to numerical simulations in comparison with soil test data. An in-depth discussion is carried out on several key issues related to the thickness effects on the time-dependent compression behaviour of clays. The arguments of Hypothesis A and Hypothesis B are revisited based on the current development of constitutive theories. Three existing elastic visco-plastic (EVP) models that consider the creep compression implicitly during the whole consolidation process can perform well in predicting the settlement of clay layers with different thicknesses, and are in line with Hypothesis B. It is concluded that using existing EVP models based on porous-media continuum mechanics is a rigorous scientific method (also called “rigorous” Hypothesis B method), which is superior to the old Hypothesis A method which has logic errors and may result in unsafe underestimation of settlements.

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1 Introduction

One of the essential assumptions in Terzaghi’s one-dimensional (1D) consolidation theory is a unique relation between void ratio and effective stress. However, laboratory test data demonstrated that the volume compression of clays continues after the dissipation of excess porewater pressure, i.e., under constant effective stress [ 5 , 38 ]. In oedometer tests or constant load conditions, such observed creep compression is called secondary compression, while the compression during the dissipation of excess porewater pressure is the primary consolidation. The time-dependency of compression of clays has been extensively studied in the past decades.

However, different interpretations and hypotheses have been proposed for modelling the effective stress-strain behaviour of soils, resulting in dramatically different predictions of consolidation and settling behaviour in field conditions. In the old design methods, the settlement of a thick layer of clay in the field is usually considered to contain three parts: the instant settlement due to distortion and horizontal expansion of the soil, the primary consolidation settlement due to excess porewater pressure dissipation, and the secondary compression due to creep. For 1D compression, the instant settlement could be ignored. For the primary consolidation settlement, some researchers considered that the overall strain at the end of primary consolidation (EOP) is independent of time and thickness, and therefore the EOP stress-strain relation obtained in oedometer tests can be directly applied to the EOP settlement prediction in the field. Different from this old method, some researchers consider that clays should be modelled as a visco-plastic material. Several elastic visco-plastic (EVP) models have been developed, and the visco-plastic strain rate is considered as a function of the effective stress-strain states and histories of the soil, with consistent expressions during both primary and secondary compression.

Behind these theoretical models, there is a long-history and active debate between the so-called “Hypothesis A” and “Hypothesis B” [ 13 , 14 , 19 , 29 ]. Hypothesis B has been supported by most EVP models. However, contradictory interpretations are still frequently reported, confusing engineers and general researchers. A recently developed EVP model by Yuan and Whittle [ 50 ] was considered to cover both hypotheses with different parameters, while other EVP models are usually only associated with Hypothesis B. It would be interesting to compare the similarities and differences between the current models, and to clarify their matches with Hypotheses A or B for typical cases.

In this study, a thorough comparison will be conducted among existing mainstream theories with different key assumptions and interpretations. The existing methods will be implemented to simulate the consolidation behaviour of clayey soils reported by the literature. Discussions will be conducted on the simulation results and the fundamental issues regarding soft soil modelling methods and the two contradicting hypotheses.

2 Existing methods for analysing creep of clays

Creep is a common phenomenon for many engineering materials, especially for clayey soils. There are different explanations for the mechanism of creep in clayey soils, most of which have been centralized on the existence of viscous bound water, i.e., the diffuse double layer between particles and inside the inter-particle microvoids. The continuous creep of the soil skeleton under constant effective stress is mainly attributed to the viscous process of bound water movement, inter-particle contact sliding, and particle rearrangement [ 21 , 33 ].

Taylor and Merchant [ 38 ] presented a differential equation to describe the compression of soils considering the change of void ratio as a function of both effective stress increment and time:

where \(e\) is the void ratio, \(t\) is time, \(\sigma^{\prime}\) is the effective stress (originally denoted as \(p\) ). They suggested that the term for partial derivative of void ratio on time, \(\frac{\partial e}{{\partial t}}\) , should “follow a law resembling that for viscous flow or creep”. However, \(\frac{\partial e}{{\partial t}}\) during the primary consolidation cannot be measured directly since the other term \(\frac{\partial e}{{\partial \sigma^{\prime} }}\frac{{\partial \sigma^{\prime} }}{\partial t}\) is non-zero. Therefore, proper mathematical models need to be proposed and verified. To date, there are mainly two categories of methods: the unique EOP theory and the EVP models.

2.1 Unique EOP: the old Hypothesis A method

To solve Eq. ( 1 ), the old method is to ignore the effect of creep during primary consolidation. A more sophisticated assumption for this method is that although creep may happen during the primary consolidation, somehow it does not affect the unique stress-strain (void ratio) relationship of the soil at EOP state [ 27 , 28 , 29 , 30 , 31 , 32 ]. This method divides the total compression into “primary consolidation” and “secondary compression”, as shown in Fig. 1 . The void ratio at EOP is unique, independent of the period required. To guarantee this, the two terms \(\frac{\partial e}{{\partial \sigma^{\prime} }}\frac{{\partial \sigma^{\prime} }}{\partial t}\) and \(\frac{\partial e}{{\partial t}}\) before EOP should be highly interdependent and their relative contributions to the total settlement at EOP are fixed. A thicker soil layer requires a longer period of consolidation and smaller \(\frac{\partial e}{{\partial t}}\) before EOP.

Conceptual diagram for of the unique EOP theory

Given the unique EOP, the creep deformation before EOP need not be analysed. The secondary compression caused by creep after EOP is calculated by:

where \(S\) is the settlement of the soil layer, \(L_{0}\) is the initial thickness, \(e_{0}\) is the initial void ratio, \(t\) is the time elapsed from load application, \(t_{p}\) is the time of primary consolidation, \(C_{\alpha }\) is the secondary compression coefficient. Equation ( 2 ) will predict parallel consolidation curves ( \(e - \log t\) ) of different thicknesses, with identical EOP strain and parallel secondary lines, corresponding to the “curve A” described by Ladd et al. [ 19 ], as shown in Fig. 2 . Therefore, the method is also termed “Hypothesis A method”.

Conceptual diagram for consolidation settlement curves of clays with different thicknesses

The Hypothesis A method is convenient for engineers, and it was claimed that this assumption of “unique EOP” is supported by many test data [ 30 , 32 ]. However, some researchers have challenged such conclusions and provided opposite interpretations [ 5 , 9 , 14 ].

2.2 Elastic visco-plastic constitutive models

The second method for modelling the creep behaviour of clays is using visco-plastic constitutive equations, where the plastic deformation of the soil skeleton is considered time-dependent or rate-sensitive. During consolidation, the total deformation of the clays is coupled with the dissipation of porewater pressure. Therefore, it can also be called a “rigorous” method.

2.2.1 Models based on equivalent time lines and isotache

Bjerrum [ 3 ] proposed the concepts of “instant compression” and “delayed compression” to replace the interpretation of primary and secondary consolidation, and described a family of time lines to describe the time-dependent compression, as shown in Fig. 3 . Yin and Graham [ 46 , 47 , 48 ] further proposed and developed the concepts of instant time line, reference time line, and equivalent time lines into a 1D elastic visco-plastic model, as shown in Fig. 4 . The vertical strain \(\varepsilon_{z}\) of a soil element under 1D compression condition can be described by:

where \(\sigma^{\prime}_{z}\) is the effective vertical stress, \(t_{0}\) is a reference time, \(t_{e}\) is the equivalent time, \(\lambda\) is the slope of the normal compression line (reference time line), \(\left( {\sigma^{\prime}_{r0} ,\varepsilon_{r0}^{{}} } \right)\) is a fixed point on the reference time line, \(\psi\) is the creep coefficient. The vertical visco-plastic (creep) strain rate \(\dot{\varepsilon }_{z}^{vp}\) can be derived as:

Illustration of the instant and delayed compression strain coupled with consolidation

Conceptual diagram for a 1D EVP model based on equivalent time or isotache

The model depicts a unique relationship between creep rate \(\dot{\varepsilon }_{z}^{vp}\) (or \(t_{e}\) ), effective stress, and vertical strain (or void ratio). Meanwhile, the elastic deformation of clays is described by the “instant time line”, which can be expressed as:

where \(\kappa\) is the slope of instant time line (recompression line in the Cam-Clay model).

Another popularly used model is the Soft Soil Creep (SSC) model developed by Vermeer and Neher [ 40 ] based on Den Haan [ 10 ]. The model follows Bjerrum's [ 3 ] interpretation of creep, and describes the creep strain rate by the current effective stress and updated pre-consolidation pressure, which can be written as:

where \(\lambda^{*} ,\kappa^{*} ,\mu^{*} ,\tau\) are constant parameters and equivalent to \(\frac{\lambda }{1 + e},\frac{2\kappa }{{1 + e}},\frac{\psi }{1 + e},t_{o}\) in Yin and Graham’s EVP model [ 46 ]. \(\sigma^{\prime}_{p}\) is the pre-consolidation pressure which is changing as soil compresses, as shown in Fig. 4 . The strain \(\varepsilon\) used by Vermeer and Neher [ 40 ] and Den Haan [ 10 ] is a logarithmic strain instead of an engineering strain. However, when ignoring this difference and considering small-strain conditions, \(\lambda^{*} ,\kappa^{*} ,\mu^{*}\) can be approximated as \(\frac{\lambda }{{1 + e_{0} }},\frac{2\kappa }{{1 + e_{0} }},\frac{\psi }{{1 + e_{0} }}\) respectively in Yin and Graham’s 1D EVP model.

Both EVP models by Yin&Graham and Vermeer&Neher accord with the “isotache” concept developed since Šuklje [ 37 ], which refers to separated stress-strain curves under different rates of strain, and therefore the models are sometimes called “isotache-type” models. There are also other EVP models [ 1 , 4 , 11 , 12 , 16 , 18 , 26 , 49 ] developed based on such an idea. Although expressed in various mathematical formulas, these models all depict that the visco-plastic strain rate is dependent on the current effective stress-strain state of the soils, but independent of the loading paths or degree of consolidation.

2.2.2 Model beyond isotache–MIT-SR

Beyond the widely used “isotache-type” models, Yuan and Whittle [ 50 ] established a 1D EVP model considering strain rate effects and temporal effects with different methods. The complete formulations considering 3D stress-strain condition have been developed based on this 1D model, namely MIT-SR model [ 51 ]. It was considered that the visco-plastic strain rate of clays is not only dependent on the current effective stress and void ratio state, but also influenced by the memory of the soil skeleton. Under 1D compression, the visco-plastic strain rate can be expressed as:

where \(R_{a}\) is an independent variable called “internal strain rate”, \(\overline{\sigma }^{\prime}_{p}\) (originally denoted as \(\sigma^{\prime}_{p}\) by Yuan and Whittle) is the yielding stress dependent on void ratio. It should be noted that \(\overline{\sigma }^{\prime}_{p}\) in Eq. ( 7 ) corresponds to the stress on the reference compression line (termed “limiting compression curve”, LCC) at the current void ratio, as shown in Fig. 5 , which is slightly different from \(\sigma^{\prime}_{p}\) in Eq. ( 6 ). \(R_{a}\) represents the history effects of visco-plastic straining, which evolves with time following a first-order differential equation:

where \(f\left( {\dot{\varepsilon }} \right)\) is an activation function for applied total strain rate \(\dot{\varepsilon }\) , \(m_{t}\) is a transient coefficient. Equation ( 8 ) allows \(R_{a}\) to transit smoothly from \(R_{a0}\) to \(f\left( {\dot{\varepsilon }} \right)\) with time. \(f\left( {\dot{\varepsilon }} \right)\) represents a steady state of the soil, which is formulated as:

Conceptual diagram for the 1D MIT-SR model by Yuan and Whittle [ 50 ]

And the mathematical expression of \(m_{t}\) is given by Yuan and Whittle [ 50 ] as:

where \(\rho_{r} = \kappa /e\) and \(\rho_{c} = \lambda /e\) are the slopes of the swelling line and normal compression line respectively in \(\ln e - \ln \sigma^{\prime}_{z}\) coordinate, \(\dot{\varepsilon }_{{{\text{ref}}}}\) is the reference strain rate adopted in constant-rate-of-strain (CRS) tests, \(\beta\) is the parameter describing the rate-sensitivity of compression lines from CRS tests.

Figure 6 presents the parametric studies on the compression curves of San Francisco Bay Mud based on CRS test data [ 17 , 50 ]. Parametric studies are carried out to reveal the effects of different \(\beta\) and \(\rho_{\alpha }\) . It can be found that \(\beta\) mainly controls the rate sensitivity in the steady state, while \(\rho_{\alpha }\) controls the transient behaviour beyond the steady state, including the significant overshooting behaviour. When \(\beta = 0\) , the compression curves at steady-state converge regardless of strain rates. For the isotache-type model discussed earlier, the strain rate is directly controlled by the stress-strain state, and there is no transient effect, which corresponds to the case of \(\beta = 0.065\) and \(\rho_{\alpha } = 0.017\) (i.e., \(\beta = \frac{{\rho_{\alpha } }}{{\rho_{c} }}\) ) and the steady state of all cases.

Parameter studies of a CRS test simulated by the 1D MIT-SR model with a different \(\rho_{\alpha }\) and same \(\beta\) ; b different \(\beta\) and same \(\rho_{\alpha }\)

Table 1 summarizes the similarities and differences between the formulations of Yuan and Whittle’s MIT-SR model versus Yin and Graham’s EVP model as a representative of isotache-type model. The MIT-SR model contains more parameters related to creep, including \(\beta\) for rate-sensitivity, \(\rho_{\alpha }\) for temporal transient behaviour of \(R_{a}\) , and \(\dot{\varepsilon }_{ref}\) as the reference strain rate. \(R_{a0}\) is an input initial value of \(R_{a}\) . While the isotache-type models have fewer parameters and are easier to use, the MIT-SR model is able to describe the nonlinear transient and overshooting behaviour of clays during the change of strain rates in CRS tests, as shown in the last row of Table 1 .

3 Comparisons of settlement calculations for clays with different thicknesses

The consolidation of clays with different thicknesses is a core issue in studying the time-dependent behaviour of clays. In this section, the interpretations of different existing models will be compared. The four different models/theories presented in the previous section are adopted for comparison considering their representativeness: (1) the unique EOP method, which is also referred to as “Hypothesis A method”, was widely used in conventional design; (2) Yin and Graham’s 1D EVP model, an isotache-type model, which is one of the earliest works and convenient to use in both simple methods and numerical simulations; (3) Vermeer and Neher’s SSC model, another isotache-type model, which is popular in PLAXIS software; (4) Yuan and Whittle’s 1D MIT-SR model, a new non-isotache EVP model.

3.1 Implementation of the theoretical models

3.1.1 numerical simulation.

In our previous simulation of CRS tests, the soil was treated as an element without boundary effects and excess porewater pressure dissipation. To study the consolidation settlement of soils with different thicknesses, hydro-mechanical coupled finite element analyses with different EVP models are implemented. The consolidation governing equations describing creep by incorporating the EVP models developed by Yin and Graham [ 46 , 47 ] and Yuan and Whittle [ 50 ] are composed of a set of partial differential equations (PDEs). To obtain the numerical solution, the coupled governing equations are implemented in the PDE modules of the commercial Multiphysics programme, COMSOL. This software offers a user-friendly interface for solving user-defined PDEs utilizing the finite element method. Within the PDE module of COMSOL, a range of PDE types are available and the coefficient-type PDE is selected to tackle the governing equations. Firstly, through adjustment of the PDE coefficient in COMSOL, the coupled governing equations can be effectively implemented. The initial and boundary conditions are established based on the initial stress state and drained conditions ensuring consistency with the simulated consolidation test. The consolidation governing equations are then discretized using the Galerkin method and solved by applying the differential algebraic equation solver in COMSOL. The SSC model by Vermeer and Neher is available in another commercial finite element programme PLAXIS.

3.1.2 Spreadsheet calculation

The conventional approach based on Hypothesis A and the unique EOP concept is implemented by Excel spreadsheet with Terzaghi’s 1D consolidation theory and Eq. ( 2 ). For Yin and Graham’s 1D EVP model, a spreadsheet calculation method has been developed as well [ 44 , 45 ]. The method is called a “simplified Hypothesis B method”, in which the total settlement of a soil layer under a load increment is calculated as:

where \(U\) is the average degree of consolidation calculated with Terzaghi’s consolidation theory, \(S_{f}\) is the settlement under final effective stress without considering any creep effects of the \(e - \log \sigma^{\prime}_{z}\) curves, \(S_{{{\text{creep}}}}\) is the creep settlement, which is calculated as:

where \(\alpha\) is an empirical parameter (usually 0.8), \(t_{ef}\) is the value of equivalent time at the stress-strain state to \(S_{f}\) under final effective stress, \(t_{{{\text{EOP}}}}\) is the EOP duration in the field, which is the same as \(t_{p}\) .

3.2 Settlement prediction

3.2.1 thickness effects on consolidation: a numerical illustration.

The consolidation problem of Osaka marine clay has been investigated and reported in the literature. With a liquid limit of around 80–100% and plastic limit of 30–40%, a clay fraction up to 40% constituted by smectite, chlorite, kaolin, illite, and mixed layered minerals, the Osaka marine clay exhibited high plasticity and significant time-dependency [ 39 , 41 , 42 , 43 , 50 ]. To investigate the effects of thickness on the consolidation of clays, Watabe et al. [ 42 ] conducted inter-connected consolidometer tests on intact Osaka marine clay samples (Ma11) with four different thicknesses 20 mm, 50 mm, 200 mm, and 400 mm. Nevertheless, the original test showed contradictory results, without a clear trend. One of the reasons might be the impurities and inhomogeneity that were inevitable for intact samples. Yuan and Whittle [ 50 ] calibrated the parameters for Ma11 based on the results of Watabe et al. [ 42 ]. Two sets of parameters were obtained based on two different specimens. Here only one set of parameters based on the 20-mm-thickness specimen is used for comparison, as summarized in Table 2 (case a). The parameters can be translated to relevant parameters in other models. For Yin and Graham’s EVP model, the soil parameters can be calculated as:

where \(n = \frac{e}{1 + e}\) is the porosity of the soil and can be estimated as the constant initial void ratio \(e = 1.23\) for the 20-mm-specimen in Watabe et al. [ 42 ]. For Vermeer and Neher [ 40 ]’s SSC model, the soil parameters can be calculated as:

For the old Hypothesis A method or the unique EOP theory by Mesri et al., the settlement curves were computed using Terzaghi’s 1D consolidation equation with a constant compressibility \(m_{v}\) for different thicknesses. The value of \(m_{v}\) is calculated from the 20-mm-specimen in Watabe et al [ 42 ]. The strain increment under loading increment from 489 to 1080 kPa is around 0.06, which yields \(m_{v} = \frac{{\Delta \varepsilon_{z} }}{{\Delta \sigma^{\prime}_{z} }}\) =0.000102 kPa −1 . The secondary compression coefficient \(C_{\alpha }\) is determined as \(C_{\alpha } = \rho_{\alpha } \cdot e \cdot \ln 10\) (Yuan and Whittle [ 50 ]). According to the CRS test, Ma11 exhibits isotache-type behaviour and \(\beta = \frac{{\rho_{\alpha } }}{{\rho_{c} }}\) , as shown in Fig. 7 . Other parameters are the same as Yuan and Whittle [ 50 ], as listed in Table 2 . The 1D MIT-SR and 1D EVP models are both implemented by COMSOL, while the SSC model is implemented in PLAXIS. The Hypothesis A method is used with Excel spreadsheets.

Calibration of β in MIT-SR model for Ma11 and Ma13Re from CRS tests (after Yuan and Whittle [ 50 ])

Figure 8 a shows the simulation results of clay consolidation with different models, including the case (a) for MIT-SR model. It can be found that all three EVP models produce highly consistent results with the parameters in Table 3 . The EOP strains increase with thickness, and exhibit similarity for three EVP models, as marked in the figure. The simulation results validate the theoretical statement in Yuan and Whittle [ 50 ] that MIT-SR model is consistent with isotache-type models with \(\beta = \frac{{\rho_{\alpha } }}{{\rho_{c} }}\) . In contrast, the Hypothesis A method predicts EOP strain independent of thickness and the strain-time curves parallel after EOP.

Simulation of consolidation settlement for intact Osaka clay with different thicknesses by different methods: a original case \(\beta = \rho_{\alpha } /\rho_{c}\) ; b parametric case \(\beta = 0.015 < \rho_{\alpha } /\rho_{c}\)

Yuan and Whittle [ 50 ] indicated that the value of \(\beta\) which can be smaller than \(\frac{{\rho_{\alpha } }}{{\rho_{c} }}\) , and showed an extreme case with \(\beta = 0\) for Osaka Clay exhibiting identical EOP strain. However, according to Yuan [ 52 ], the values of \(\beta\) for several clays worldwide are all larger than 0.01, and it is \(\beta = 0.015\) for reconstituted Osaka Bay clay (Ma13Re), as shown in Fig. 7 . In this study, \(\beta = 0.01\) 5 is used as another typical case to compute the consolidation settlement of the Osaka clay. According to the MIT-SR model, the creep of soil is influenced by \(\beta ,\rho_{\alpha } ,\dot{\varepsilon }_{ref}\) . If \(\beta \ne \frac{{\rho_{\alpha } }}{{\rho_{c} }}\) , the other parameters should be re-estimated by matching the test data. In this study, it was found that adopting \(\rho_{\alpha } = 0.015\) and \(\dot{\varepsilon }_{ref} = 0.0072\;\% /{\text{h}}\) can generally match the consolidation curves. The simulation results based on this set of parameters are shown in Fig. 8 b. It is found that the consolidation curves by MIT-SR model deviate from the other two EVP models, seeing a slower convergence trend. However, the EOP strains are still influenced by the thickness of the soils, and the settlement curves of different thicknesses gradually join into one line with increasing time. The simulations on the two cases show that for typical cases, the non-unique EOP behaviour is obvious in EVP modelling.

3.2.2 Consolidation analysis for a thick reconstituted clay specimen

The data on Ma11 are not used to verify any of the methods because they did not show a consistent trend that existing methods can explain with a consistent parameter set. The reason is unclear but can be related to the quality of natural samples. Considering the size of the specimens, the existence of possible impurities cannot be neglected. Fortunately, Watabe et al. [ 42 ] reported a consolidation test on reconstituted Osaka marine clay (Ma13Re) specimens, which should be much more uniform and properly controlled compared to the natural ones. In this study, the data of Ma13Re will be used to verify the existing model predictions. The parameters of the Ma13Re can be determined by a multistage oedometer test [ 43 ] and a CRS test [ 39 ] on the same soil.

The values of \(\beta\) and \(\rho_{\alpha }\) in MIT-SR model have been calibrated by Yuan [ 52 ] from the CRS test on MA13Re by Tsutsumi and Tanaka (2012), as listed in Table 3 . It can be found that different from the intact Ma11, the fitted values of \(\beta\) of Ma13Re is not equal to \(\frac{{\rho_{\alpha } }}{{\rho_{c} }}\) . Other parameters including those for the EVP and SSC models are calibrated from an oedometer test reported by Watabe et al. [ 43 ]. The results of this oedometer test and the \(e - \log \sigma^{\prime}_{z}\) curve at both EOP and 24 h are replotted in Fig. 9 . The pre-consolidation pressure \(\sigma^{\prime}_{p0}\) was 134 kPa for the oedometer specimen and 116 kPa for the 100 mm specimen [ 42 , 43 ]. Based on the 1-day compression curve, the normal compression line \(\lambda\) and the slope of over-consolidation line \(\kappa\) from 88 to \(\sigma^{\prime}_{p0}\) can be fitted. The creep coefficient \(\psi\) is fitted using the \(e - \ln t\) relations at the secondary compression stage of the specimen under 275 kPa. The EOP void ratio-stress curve was used to determine the strain increment and compressibility for the Hypothesis A method. The permeability \(k_{v}\) is assumed to follow a correlation with void ratio: \(k_{v} = k_{vi} 10^{{\frac{{e - e_{i} }}{{C_{k} }}}}\) . Since the permeability of Ma13Re was not measured by Watabe et al., it is assumed here based on the measured data of Ma11, with \(k_{vi} = 2.55 \times {10}^{{ - 8}} {\text{cm/s, }}C_{k} = 1.15, \, e_{i} = 1.3\) based on Yuan and Whittle [ 50 ].

1D compression curves of Ma13Re (20 mm oedometer specimen) for model calibration: a in \(e - \ln t\) plane; b in \(e - \ln \sigma^{\prime}_{z}\) plane; c in \(\ln e - \ln \sigma^{\prime}_{z}\) plane (after Watabe et al. [ 43 ])

Figure 10 shows the calculated settlement curves of Ma13Re using different methods and models. The old A method using unique EOP strain underestimates the settlement. Using three EVP models and the simple B method with parameters calibrated from the oedometer or CRS tests, the prediction settlement curves all fit well with the measured data. Some differences exist in the prediction results, which are probably due to the different formulations and numerical tools among the models. For example, the MIT-SR uses logarithmic void ratio, the SSC model uses logarithmic strain, while Yin & Graham’s EVP model uses engineering strain. The Yin & Graham’s EVP model and MIT-SR model are implemented by COMSOL, while the SSC is implemented by PLAXIS.

Simulation of consolidation settlement for Ma13Re with different methods

Although the loading scheme of the oedometer test was different from the 100mm consolidation test, the settlement curves of Ma13Re under oedometer set-up (20 mm, 2-way drainage) can still be estimated using Terzaghi’s equation, and plotted in Fig. 10 . For the standard oedometer specimen, Hypotheses A and B should yield similar results. Comparing the settlements of two thicknesses, the EOP strain of the 100 mm specimen is significantly larger than the EOP strain for the oedometer specimen. The MIT-SR model slightly overestimates during primary consolidation but offers the best matching with measured data at the secondary compression stage. The test results on Ma13Re and all EVP models’ predictions are in line with Hypothesis B.

4 Discussions on the key questions about consolidation and creep

With a number of methods and models developed in the literature, they have provided different answers to some well-known and long-history questions, including the famous debate between “Hypothesis A” and “Hypothesis B”. The debate is concerned with a series of questions, which were frequently inconsistently interpreted.

4.1 Whether creep happens in primary consolidation

To model the time-dependent compression of clays, the first fundamental problem is to answer whether creep can happen during the “primary” consolidation. Primary consolidation refers to the process in which excess porewater pressure of a soil layer dissipates with time until it gets zero. In many old design methods, such as the FHWA-NHI-06-088 in USA [ 35 ], the settlement was divided into primary consolidation and secondary settlement. The primary consolidation settlement was analysed directly using the compressibility measured on thin specimens in the laboratory, as indicated in Fig. 1 . The secondary compression due to creep after EOP is calculated using the same method as Eq. ( 2 ), while creep during the primary consolidation is not calculated. Under the influences of this method, it was frequently interpreted by many engineers and researchers that creep does not exist before EOP.

Although the old Hypothesis A method was still popular with engineers due to the convenience of usage, nowadays more researchers agree or imply that the effects of creep, or visco-plastic deformation, should be considered during and after primary consolidation [ 3 , 9 , 14 , 15 , 22 , 29 , 38 , 46 , 50 ]. It was also pointed out that assuming no creep during primary consolidation violates the continuum mechanics [ 15 , 36 ]. In general, creep can be deemed as a result of structure viscosity of the soil skeleton or other mechanisms in the microstructures [ 21 , 33 ], which is coherent during the whole consolidation process, instead of just happening after EOP, as indicated in Eq. ( 1 ). As shown in Fig. 6 and Table 1 , both isotache- and non-isotache-type models consider the rate-dependent behaviour during CRS consolidation process.

4.2 Whether creep is a separate phenomenon during primary consolidation

Ladd et al. [ 19 ] first questioned “whether creep acts as a separate phenomenon while excess pore pressures dissipate during primary consolidation”, and it was interpreted that the “rheology models” considered creep as a separate phenomenon due to the structural viscosity of soils. In the representative EVP (rheology) models discussed in previous sections, creep is a spontaneous behaviour caused by the visco-plastic property of clays, but is also dependent on the effective stress, void ratio [ 40 , 46 ], and the history of strain rates [ 50 ], which is not totally isolated during the primary consolidation. In the unique EOP theory, the creep rate must be associated with the degree of consolidation to achieve a unique EOP strain [ 31 ]. Both the rheology models and unique EOP theories considered creep dependent on the consolidation process. A more precise statement may be “rheology models consider creep as a spontaneous behaviour, which is not controlled by EOP but dependent on the consolidation process”.

4.3 Whether EOP strain relationship is thickness-dependent

4.3.1 interpretation of unique eop theory and isotache-type models.

Some researchers insist that despite creep may exist during primary consolidation, it will not affect the unique EOP stress-strain relations of soils [ 27 , 29 , 31 ]. If this hypothesis stands as a general rule, there will be no need to analyse the creep compression during the primary consolidation, and the EOP strain of clays with different thicknesses is identical under the same initial state and load increment, as shown in Fig. 8 . Therefore, it predicts the same results with the simple hypothesis that creep does not exist during primary consolidation. If this is true, the determination of EOP will be a key factor in the creep estimation. It still needs clarification why the visco-plastic compression of the soil is dependent on the thickness of the soil layer. Besides, since the consolidation near EOP becomes extremely slow, the estimated value of EOP period naturally contains a large margin of error. Furthermore, it was also noted that some researchers [ 7 , 8 , 9 , 36 ] have re-analysed a number of test data reported in the literature considering the stress-strain histories before the incremental loading. The results showed that many consolidation test data that were considered to reveal the unique EOP behaviour actually inclined towards non-unique EOP or the isotache-type models.

In contrast, some researchers concluded that if creep exists within primary consolidation, it will contribute to the total compression of soils before EOP and should be modelled before EOP. Therefore, the EOP strain of the same soils is dependent on the \(t_{p}\) . The larger the thickness of clay, the larger the value of \(t_{p}\) , and the larger the EOP strain. Such behaviour is predicted by the EVP model by Yin & Graham and the SSC model, as shown in Figs. 8 , 9 .

4.3.2 Interpretation of MIT-SR model

Special attention is given to the prediction results of the non-isotache MIT-SR model by Yuan and Whittle [ 50 ]. Figure 11 shows the simulation results by MIT-SR model considering different values of parameters \(\beta\) and \(\rho_{\alpha }\) . The soil is an NC clay and the parameters follow the simulation by Yuan and Whittle [ 50 ], but the values of \(\beta\) and \(\rho_{\alpha }\) are changed. It can be found that the configurations of consolidation curves are evolving with \(\beta\) and \(\rho_{\alpha }\) adopted. In Fig. 11 a, when the upper bound \(\beta = \frac{{\rho_{\alpha } }}{{\rho_{c} }}\) is adopted, the EOP strain significantly increases with soil thickness, and the consolidation settlement curves converge quickly after EOP, with the same pattern as the isotache-type models. In Fig. 11 b-c, as \(\beta\) deviates from \(\frac{{\rho_{\alpha } }}{{\rho_{c} }}\) and decreases, the convergence point is delayed, the secondary compression slope becomes smaller, and the difference of EOP strains becomes smaller. However, as long as \(\beta > 0\) , including in the cases of Fig. 8 , the strain-time curves of different thicknesses always converge, and the EOP strain always increases with thickness. For the extreme case of Fig. 11 d where \(\beta = 0\) , the EOP strains of different thicknesses are the same, and the secondary compression curve seems non-converged after a long period. Such results look similar to the predictions by the unique EOP theory and the Hypothesis A method.

Simulation of consolidation settlement by 1D MIT-SR model with different values of β and \(R_{a0}\) : a \(\beta = 0.047 = \rho_{\alpha } /\rho_{c}\) ; b \(\beta = 0.03 < \rho_{\alpha } /\rho_{c}\) ; c \(\beta = 0.0094 < \rho_{\alpha } /\rho_{c}\) ; d \(\beta = 0 < \rho_{\alpha } /\rho_{c}\) ; e \(\beta = 0 < \rho_{\alpha } /\rho_{c}\) with \(R_{a0}\) proportional to \(1/H^{2}\)

However, \(\beta = 0\) suggests that in CRS tests, the soil would not exhibit rate sensitivity at steady state. According to the calibration results on various types of reconstituted and intact clay samples from Boston, San Fransisco, and Osaka [ 50 , 52 ], the values of \(\beta\) ranged between 0.01 and \(\frac{{\rho_{\alpha } }}{{\rho_{c} }}\) , but none reached zero. Therefore, the case of \(\beta = 0\) in Fig. 11 d is unlikely to be suitable for clays. Besides, the \(e - \log \sigma^{\prime}\) curves during the consolidation are influenced by the value of \(R_{a0}\) , as shown in Fig. 11 d-e. Under a special case, when \(R_{a0}\) of 200-mm-specimen is 1/100 \(R_{a0}\) of 20 mm-specimen (i.e., \(R_{a0} \propto\) \(\frac{1}{{H^{2} }}\) ), their \(e - \log \sigma^{\prime}\) relations overlapped. However, such results do not indicate the absence of creep during primary consolidation. If other values of \(R_{a0}\) is used, the \(e - \log \sigma^{\prime}\) curves will exhibit dependency of thickness, which differs from the old Hypothesis A method.

Therefore, results like Fig. 11 d-e are limited to extreme conditions, and there is no such evidence showing \(\beta = 0\) from laboratory test data on clays. In fact, one might note that the case of \(\beta = 0\) coincides with the compression behaviour of sands, which usually exhibit temporal effects but no isotache-type behaviour [ 2 , 20 , 25 ]. Figure 12 shows the compression curves of dense Cologne sand subjected to CRS tests [ 23 , 24 ]. It can be found that for the sand, the configuration of compression curves is similar to the case \(\beta = 0\) in Fig. 6 b. The steady-state stress-strain curve of the sand is not sensitive to strain rates. However, it did exhibit temporal effects, including the transient effect during the changes of compression rate, as well as the creep compression under constant loading and therefore \(\rho_{\alpha } > \beta = 0\) . In this regard, the MIT-SR model has achieved remarkable advances in modelling some time-dependent behaviour of different types of soils that conventional isotache-type models could not explain.

CRS test results of a dense sand specimen exhibiting transient but non-isotache behaviour (after Levin et al. [ 24 ])

4.3.3 Interpretation with variable initial conditions

The above discussion is based on the premise that the soils with different thicknesses are uniform with the same initial conditions, such as the initial void ratio. If the initial conditions are different, the compression under the same loading will be different. Figure 13 shows the results of SSC modelling on the same clay with the initial void ratio ( \(e_{0}\) ) of the 200-mm-specimen varying between 2.51, 2.56, and 2.61. It can be found that in terms of vertical strain, the consolidation curves do not converge and exhibit some similar pattern as the curve A in Fig. 2 , although the void ratio is changed by only 0.05–0.1. As soil is a natural material, such problem could have occurred in previously reported tests. The inconsistent initial void ratio can be another interpretation of test results that were similar to “curve A” in Fig. 2 . But in terms of void ratio or accumulative strain, the isotache-type models will predict “curve B” only. Previous researchers have successfully used EVP models to explain this issue [ 7 , 36 ].

Simulation of consolidation settlement by SSC model with different initial void ratios: a by incremental strain; b by void ratio

4.3.4 Non-uniqueness of EOP and convergency of secondary compression curves

In Fig. 2 , the “curve A” has a unique EOP strain and parallel secondary compression curves after EOP, while the “B curve” exhibits non-unique EOP together with immediately converging secondary compression curves with different thicknesses. It should be noted that in some cases, non-unique EOP may not fully correspond to immediately converging secondary compression curves after EOP. For example, in the predictions by MIT-SR in Fig. 11 b-d, the EOP void ratios are apparently different for different thicknesses, but the secondary compression curves do not converge immediately as described in Fig. 2 . In Fig. 13 , the soils with different initial void ratios have non-converging secondary compression curves after EOP, but the EOP strains are still different.

4.4 Hypothesis A or Hypothesis B: a revisit

4.4.1 current contradictions.

As discussed previously, Ladd et al. [ 19 ] stated that if creep is a separate phenomenon due to the structural viscosity of soils, the EOP strain will be dependent on the primary consolidation duration. Otherwise, the EOP strain will be unique. A conceptual figure was presented with two “extreme curves”, in which “curve A” describes unique EOP while “curved B” represents the results from rheologic models with increasing EOP strain with increasing thickness, as shown in Fig. 2 . However, Ladd et al. [ 19 ] did not provide a direct definition of Hypothesis A and Hypothesis B.

After Ladd et al. [ 19 ], the terms “Hypothesis A” and “Hypothesis B” were firstly defined by Jamiolkowski et al. [ 13 ], co-authored by Prof. Ladd. It was concluded that Hypothesis A assumes creep occurring only after primary consolidation, while Hypothesis B assumes creep occurring during pore pressure dissipation due to structural viscosity. Such interpretations were then widely used [ 14 , 22 , 42 , 45 , 48 ], which appeared to be a very simple criterium to define these two hypotheses. With this definition, the procedure used by the conventional design method [ 35 ] corresponds to Hypothesis A, while the methods based on EVP (rheology) models by Leroueil et al. [ 22 ], Kavazanjian et al. [ 15 ], Yin and Graham [ 46 , 47 , 48 ], Vermeer and Neher [ 40 ], Degago et al. [ 9 ], Yuan and Whittle [ 50 ], all correspond to Hypothesis B.

Nevertheless, there was another interpretation of Hypotheses A and B, based on whether or not the EOP strain is unique for the same soils with different thicknesses [ 9 , 36 ]. According to Szavits-Nossan [ 36 ], both Hypotheses A and B now accepted that creep can occur during primary consolidation, but Hypothesis A advocates unique EOP strain while Hypothesis B does not. For example, despite acknowledging creep during primary consolidation, the theories advocating unique EOP stress-strain relationship by Mesri et al. [ 30 , 32 ] are also categorized and claimed to be Hypothesis A. With this hypothesis, the creep deformation during primary consolidation need not be calculated, which produces the same results as the simple assumption that creep does not exist before EOP. On the contrary, Hypothesis B, represented by most EVP models, considers that the EOP strain is not unique and will be affected by the creep compression during primary consolidation. Before the invention of MIT-SR model, the two definitions converged and their differences were seldom discussed.

As discussed previously, the MIT-SR model considers creep during primary consolidation, but can simulate “curve A” with unique EOP strain when \(\beta = 0\) as shown in Fig. 11 e, although \(\beta = 0\) is more suitable for sands. Yuan and Whittle [ 50 ] commented that the case \(\beta = 0\) corresponds to Hypothesis A behaviour while \(\beta = \frac{{\rho_{\alpha } }}{{\rho_{c} }}\) corresponds to Hypothesis B behaviour, as shown in Fig. 11 a. According to the simulations in this study, when \(\beta > 0\) for general clayey soils, including Osaka clay, the predictions are all supportive of non-unique EOP, as shown in Fig. 11 a-c. Even in the case with a very small value of \(\beta\) (around 0.01) in Fig. 11 c, the settlement curves of the clays with different thicknesses exhibit a slower converging trend compared to \(\beta = \frac{{\rho_{\alpha } }}{{\rho_{c} }}\) , but still indicate “non-unique EOP” and converging trend. If the criterion of “whether EOP is unique” is followed, it seems that the MIT-SR model corresponds to Hypothesis B for clayey soils (Fig. 11 a-c) but inclines towards Hypothesis A for sands (Fig. 11 d). Therefore, almost all cases ( \(0 < \beta \le \frac{{\rho_{\alpha } }}{{\rho_{c} }}\) ) for clays of MIT-SR model predictions indicate Hypothesis B, not limited to the single case of \(\beta = \frac{{\rho_{\alpha } }}{{\rho_{c} }}\) in Fig. 11 a.

With the development of EVP modelling from Bjerrum [ 3 ] to Yuan and Whittle [ 50 ], researchers have a growing understanding of the creep behaviour of clays. However, it can be found that there exist some contradictions regarding the usage of Hypothesis A and Hypothesis B in the literature, and such inconsistent interpretation may confuse or even mislead engineers.

4.4.2 A unified interpretation: hypothesis, methodologies, and phenomena

Figure 14 shows the relationships between the key concepts in the modelling of soil creep, which is associated with three levels: hypotheses, methodologies, and phenomena. The first set of hypotheses concerns whether creep can happen during primary consolidation. The second set of hypotheses concerns whether creep during primary consolidation can affect the EOP stress-strain relationship. Combining the current understandings among researchers reviewed before, Hypothesis A should refer to the assumption that the EOP compression is unique and uninfluenced by creep, while Hypothesis B should refer to the idea that the compression during the whole process can be influenced by creep, to different degrees dependent on the specific viscosity parameters. Hypothesis A requires \(t_{p}\) as a parameter while Hypothesis B does not. Therefore, the three EVP models discussed here can be categorized to Hypothesis B.

Correlations between different concepts related to consolidation and creep of clays

For the methodologies, Hypothesis A is achieved by a unique EOP theory with the secondary compression calculated by Eq. ( 2 ). Separation of primary and secondary consolidation is needed in this method, which implies that creep does not exist or need not be considered during primary consolidation. Hypothesis B is achieved by hydro-mechanical coupled analysis using an elastic visco-plastic model. Different models were developed from the relatively simple isotache-type models [ 40 , 46 ] to the more complex model by Yuan and Whittle [ 50 ]. These EVP models are developed based on continuum mechanics, without direct assumptions on the position of EOP, and could be referred to as “rigorous” Hypothesis B [ 44 ].

Different results can be described by different methods and hypotheses. For the old Hypothesis A method, it is always predicted that the EOP strain of the same clay with different thicknesses is a constant, and that the secondary compression curves are parallel. For the EVP models, the EOP void ratio is dependent on many factors, including the soil parameters (such as \(\beta ,\rho_{\alpha } ,\psi\) ), the thickness, and the duration for primary consolidation. When \(\beta = 0\) in the MIT-SR model, it can predict unique EOP strain, which however is an extreme case that probably only works for sands.

4.4.3 Suggestion for design practice

Although the complex mechanisms of clay creep are not fully understood yet, it has gradually been an academic consensus on using elastic visco-plastic models for clay behaviour [ 50 ]. There are two reasons to improve the old Hypothesis A method in design codes.

Firstly, from the experimental side, the interpretations of many consolidation settlement data supporting unique EOP have been challenged and re-interpreted to show the contrasting behaviour after considering the different initial conditions [ 9 , 36 ]. From the interpretation by MIT-SR model, clayey soils tend to have non-zero \(\beta\) , which is also in line with the Hypothesis B.

Secondly, from the theoretical side, existing EVP models have been developed based on continuous mechanics, with much more versatility in describing the behaviour of clays in various hydro-mechanical conditions, without estimation of \(t_{p}\) and subjective assumptions on EOP strain. For simple analysis, the de-coupled simplified Hypothesis B method has been validated with a number of real cases, showing comparable accuracy [ 44 , 45 ]. In recent years, several countries like Canada and Norway have updated their design guidelines to include EVP modelling and Hypothesis B in the settlement analysis of clays [ 6 , 34 ]. Among three models, the isotache-type models by Vermeer and Neher [ 40 ], Yin and Graham [ 46 , 47 , 48 ] (including the simple B method [ 44 , 45 ]) have simpler forms and are easier to use, while the MIT-SR model [ 50 ] contains more versatility but also more complicated implementation.

5 Conclusions and suggestions

In this study, a comparison is conducted among four existing methods for modelling the 1D consolidation of clays exhibiting creep: the unique EOP method, Yin and Graham’s 1D EVP model, Vermeer and Neher’s SSC model, Yuan and Whittle’s 1D MIT-SR model. Numerical simulation results on typical cases are presented and key issues of researchers’ concern are discussed and revisited. The major conclusions are summarized below.

Most researchers agree that clays are viscous materials and that visco-plastic compression exists during the consolidation process. Creep is not an isolated phenomenon but is coupled with the dissipation of excess porewater pressure.

The terminologies of Hypothesis A and Hypothesis B have been frequently abused, and therefore a more precise definition is required. Hypothesis A is an assumption that the relationship between EOP void ratio and effective stress is unique and uninfluenced by the creep of soils. Hypothesis B considers that the visco-plastic compression of clays can affect the EOP strain and should be considered during primary consolidation.

For typical clayey soils, the interpretations of thickness effects by existing EVP models (including the isotache-type models and the MIT-SR model) are in line with Hypothesis B, with non-unique EOP behaviour. Hypothesis B is not limited to an “extreme” case or “isotache” models only.

All three EVP models have good performance in calculating the settlements of clays. The two isotache-type models are easier to implement, while the MIT-SR model might be more versatile in describing the creep behaviour.

Existing EVP models can partly explain the phenomenon that consolidation settlements exhibit similar EOP or non-converging trends with different thicknesses, without assuming unique EOP in Hypothesis A. In the MIT-SR model, a smaller \(\beta\) will cause the slower convergence of settlement curves, and the extreme case \(\beta\) =0 will generate consolidation curves with unique EOP, although it may be suitable for sands only. In all EVP models, the in-consistency of the initial void ratio of clay can also explain the consolidation settlement curves with different thicknesses exhibiting non-converging trends.

The old Hypothesis A method stands on a weak foundation in both experimental and theoretical interpretation. It is necessary and convenient to adopt visco-plastic models for calculating clay settlement for safer design rather than the old method.

Data availability

No datasets were generated or analysed during the current study.

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Acknowledgement

The authors would like to acknowledge Dr Yixing Yuan, one of the contributors of the MIT-SR model (Yuan and Whittle 2018), for his pre-view and advice to this article via personal discussions. We are also grateful to Prof. Andrew Whittle for the discussion on EVP models. This study is financially supported by General Research Fund (15231122, 15226722), Research Impact Fund (R5037-18), and Theme-based Research Scheme Fund (T22-502/18-R) from the Research Grants Council of Hong Kong Special Administrative Region Government, and grants (ZDBS, CD7A, CD7J, CD82, BD8U, BDS5) from Research Institute for Land and Space and The Hong Kong Polytechnic University.

Open access funding provided by The Hong Kong Polytechnic University. Research Grants Council, University Grants Committee (R5037-18, 15226722).

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Ze-jian Chen, Peng-lin Li, Pei-chen Wu, Jian-hua Yin & Ding-bao Song

Research Institute for Land and Space, The Hong Kong Polytechnic University, Hong Kong Special Administration Region, China

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Chen ZJ, Li PL and Song DB contributed to the conception, analysis, and interpretation of the data and drafted work. Yin JH and Wu PC revised the manuscript and contributed to the interpretation of the data.

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Chen, Zj., Li, Pl., Wu, Pc. et al. Study of the one-dimensional consolidation and creep of clays with different thicknesses using different hypotheses and three elastic visco-plastic models. Acta Geotech. (2024). https://doi.org/10.1007/s11440-024-02405-w

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Received : 21 December 2023

Accepted : 06 September 2024

Published : 25 September 2024

DOI : https://doi.org/10.1007/s11440-024-02405-w

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