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How to Write a Research Hypothesis- Step-By-Step Guide With Examples

Writing a research hypothesis is a pivotal step in any scientific inquiry, serving as the foundation upon which entire studies are built. Whether you're delving into the mysteries of particle physics or exploring the intricacies of human behaviour, formulating a clear and concise hypothesis is essential for guiding your research and drawing meaningful conclusions.

In this blog post, we'll understand how to write a research hypothesis that sets the stage for rigorous investigation. We'll explore what a hypothesis is, why it's important, and the key components that make up a well-formed hypothesis. From identifying the variables at play to establishing the direction of your study, we'll provide practical tips and examples to help you articulate your hypothesis with precision and clarity.

Table of Content

What is a Research Hypothesis?

Difference between a hypothesis and a prediction, types of hypothesis in research, key components of research hypothesis, hypothesis in research methodology, how to write a research hypothesis, effective tips to write a research hypothesis, research hypothesis examples.

A research hypothesis is a statement that proposes a tentative explanation for a phenomenon or relationship that is being investigated in a scientific study. It is an educated guess or prediction about the relationship between variables based on existing knowledge and theory. In essence, the hypothesis serves as a testable proposition that guides the research process by providing a clear direction for inquiry and prediction of expected outcomes.

Here are six types of research hypothesis:

Null Hypothesis (H0): This type suggests that there is no relationship or difference between the variables being studied. It's like saying, "We don't expect anything to happen." Researchers try to disprove or reject the null hypothesis to support their research hypothesis.
Alternative Hypothesis (Ha): This is the hypothesis researchers really want to prove. It suggests that there is a significant relationship or difference between the variables. It's like saying, "We expect something specific to happen."
Directional Hypothesis: It predicts the direction of the expected outcome. For example, "Eating breakfast will improve students' test scores." It specifies that one variable will lead to an increase or decrease in the other.
Non-directional Hypothesis: This type doesn't specify the direction of the expected relationship or difference, just that there is one. For example, "There is a difference in test scores between students who eat breakfast and those who do not."
Simple Hypothesis: This involves only two variables — one independent and one dependent. It's straightforward, suggesting a relationship between these two variables only.
Complex Hypothesis: This involves more than two variables, which might include multiple independent and/or dependent variables. It suggests a relationship that includes several factors interacting with each other.

A well-crafted hypothesis provides a clear direction for research, guiding the investigator's efforts to test specific predictions and draw meaningful conclusions. To create an effective hypothesis, several key components must be carefully considered and articulated. In this discussion, we'll explore these essential elements in detail.

Variables: Clearly identify the variables involved in the study. These are the factors or characteristics that can change or vary, such as age, gender, temperature, etc.
Relationship: Describe the proposed relationship between the variables. This explains how changes in one variable are expected to affect the other variable.
Directionality: Specify the direction of the expected relationship, if applicable. This indicates whether the relationship is expected to be positive (increases in one variable lead to increases in the other) or negative (increases in one variable lead to decreases in the other).
Testability: Ensure that the hypothesis can be tested through empirical observation or experimentation. It should be possible to collect data that either supports or refutes the hypothesis.
Clarity: Clearly state the hypothesis in a concise and understandable manner. Avoid ambiguity or vague language to ensure that the hypothesis is clearly understood by others.
Falsifiability: Make sure that the hypothesis is falsifiable, meaning that it is possible to prove it wrong. This is essential for scientific inquiry as it allows researchers to test and refine their hypotheses.
Relevance: Ensure that the hypothesis is relevant to the research question or problem being investigated. It should address a gap in knowledge or seek to answer a specific research question.
Guess: It's like making an educated guess about something you want to find out.
What You Think Will Happen: You're saying what you believe might be true or might happen based on what you know.
Testing Idea: It's a statement that suggests what you want to test or explore in your research.
Prediction: You're saying what you expect to see or find out when you do your research.
Clear Statement: It's a clear, specific statement that explains what you're trying to find out or prove.
Based on Prior Knowledge: It's built on what you already know or what others have found in similar situations.
Can be Proven Wrong: It's something that can be shown to be false if the research doesn't support it.
Guides Your Research: It's like a roadmap for your study, helping you focus on what's important and what to look for.
Helps Formulate Questions: It leads to questions you can ask and experiments you can conduct to find out if your guess is correct.
Foundation of Research: It forms the basis of your research, giving you a starting point to investigate and learn more about your topic.

Writing a research hypothesis involves several key steps to ensure it is clear, testable, and grounded in existing knowledge. Here's a step-by-step guide on how to write a research hypothesis:

Identify the Research Topic: Begin by clearly defining the research topic or question that you want to investigate. This could be based on your interests, gaps in existing literature, or practical problems that need addressing.
Review Existing Literature: Conduct a thorough review of relevant literature to understand the current state of knowledge in your research area. Identify key theories, concepts, and empirical findings that will inform your hypothesis.
Identify Variables : Determine the variables that are central to your research question. These include the independent variable (IV), which you manipulate or control, and the dependent variable (DV), which you measure or observe.
Formulate a Tentative Relationship: Based on your review of the literature and theoretical framework, hypothesize the relationship between the independent and dependent variables. Consider whether you expect a positive, negative, or no relationship between them.
Write the Hypothesis: Craft a clear and concise statement that articulates your research hypothesis. Use specific language to describe the relationship between the variables and the expected direction of the effect, if applicable. Ensure that the hypothesis is testable and falsifiable.
Revise and Refine: Review your hypothesis to ensure it is logical, coherent, and aligned with the research question and objectives. Revise as needed to improve clarity and specificity. Seek feedback from peers or mentors to refine your hypothesis further.
Consider Alternative Hypotheses: Anticipate alternative explanations or competing hypotheses that could account for the observed relationship between variables. Acknowledge these alternative hypotheses and explain why your proposed hypothesis is the most plausible.
Provide Justification: Briefly justify why you believe your hypothesis is reasonable and worth investigating. Draw upon evidence from the literature or theoretical rationale to support your hypothesis.
Review and Finalize: Before proceeding with your research, carefully review your hypothesis to ensure it meets all necessary criteria and accurately reflects your research aims. Make any final adjustments or clarifications as needed.

Here are 10 tips to help you write a research hypothesis effectively:

Start by identifying the key variables or factors of interest in your research question. Clearly define the specific variables that you intend to study and the relationship between them that you will be investigating. A good hypothesis focuses only on a few key, well-defined variables.
Be specific. Operationally define all the key terms and concepts clearly so your measurements and observations directly align with the concepts in your hypothesis. Ambiguous terminology can muddy hypotheses and research. Include explicit descriptions and qualifications so no aspect is open to interpretation.
State the hypothesized relationship between the main variables and the precise outcome you predict will occur. Don’t just identify variables, but propose predictive causal relationships. Frame the relationships and predicted effects in clear, descriptive language that sets up clear testing procedures. Qualify predictions appropriately based on your study parameters.
Make your hypothesis falsifiable through scientific inquiry and testing within the context of your study. A hypothesis must make predictions that have the possibility of being proven incorrect by data. An unfalsifiable hypothesis framed too vaguely can’t be rigorously put to the test.
Frame your hypothesis prediction in definitive, quantitative terms that lend themselves to statistical analysis rather than vague qualifiers. This precision sets you up to gather data that can confirm or contradict the validity of specific predictions and measure the strength of variable relationships.
Keep it simple. Do not include too many variables in your hypothesis. Stick to identifying and making predictions about the effects of two or three key independent variables on the major outcomes. Too many variables make hypotheses diffuse and research investigations unwieldy.
Detail the specific population and context your hypothesis claims apply to rather than making universal claims. Identify upfront meaningful limitations, sample characteristics, contextual qualifiers, potential confounding variables that could impact results, etc to hone the scope of the hypothesis testing.
Check if any key aspects of your hypothesis align with or contradict claims made in prior relevant studies in established literature. Citing a few studies that back parts of your hypothesis can strengthen its plausibility. Outlining contrasts also indicates familiarity with the research landscape.
Align your hypothesis closely with your intended research methods and study design to ensure you gather the appropriate data to adequately test the details of the stated hypothesis. Construct a study with power to validate your specific causal claims.
Scrutinize and thoughtfully revise your initial raw hypothesis draft multiple times to hone precision, clarity, and coherence. An unambiguous hypothesis acts as a roadmap guiding all downstream research, so ensure it is polished.

Comparing your hypothesis to those of your colleagues in the field may be the best way to determine its efficacy. When it comes to crafting an effective research hypothesis, there's no need to start from scratch. You'll read other hypotheses while you prepare your own and read them. These can provide you with advice on what should and shouldn't be included in a compelling research hypothesis. To help you get started, here are a few generic examples:

"After sixty years of age, eating an apple every day will reduce the number of doctor visits." Customer complaints are more likely to be directed towards budget airlines. An airline that provides fewer amenities and cheaper fares than a conventional full-service airline is known as a budget airline. (Note that the hypothesis uses the term "budget airline." Employee job satisfaction is higher in companies that provide flexible working hours than in those that have set hours.

The aforementioned examples are all specific, observable, and quantifiable, and standard experimental procedures can be used to either confirm or refute the prediction. However, keep in mind that as your research develops, your hypothesis will frequently change.

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How to Write a Research Hypothesis- FAQs

What is a research hypothesis.

A research hypothesis is a tentative statement that proposes a relationship between variables in a scientific study. It serves as a testable prediction about the expected outcome of the research.

How do I formulate a research hypothesis?

To formulate a research hypothesis, identify the independent variable (IV) and dependent variable (DV) in your study, specify the expected relationship between them, and consider existing theory and evidence in your field.

What makes a good research hypothesis?

A good research hypothesis is specific, testable, and grounded in existing knowledge or theory. It should be clear, concise, and capable of being either supported or refuted through empirical research.

Should I state the direction of the relationship in my hypothesis?

Depending on the nature of your research question, it may be appropriate to specify the expected direction of the relationship between variables (positive, negative, or non-directional) in your hypothesis to provide clarity and guidance.

Why is it important to write a research hypothesis?

Writing a research hypothesis is essential for guiding the research process, formulating testable predictions, and drawing meaningful conclusions. It helps researchers focus their efforts and ensures that their studies contribute to advancing knowledge in their field.

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How to Write a Hypothesis: Step-By-Step Guide

A hypothesis is a testable statement that guides scientific research. Want to know how to write a hypothesis for your research paper? This guide will show you the key steps involved, including defining your variables and phrasing your hypothesis correctly.

Key Takeaways

A hypothesis is a testable statement proposed for investigation, grounded in existing knowledge, essential for guiding scientific research.
Understanding different types of hypotheses, including simple, complex, null, and alternative, is crucial for selecting appropriate research approaches.
Crafting a strong hypothesis involves a systematic process including defining variables, phrasing it as an if-then statement, and ensuring it is clear, specific, and testable.

Understanding a Hypothesis

An empirical hypothesis is not just a simple guess. It represents a preliminary concept that stands to be scrutinized through Research and experimentation. A well-constructed hypothesis is a fundamental component of the scientific method, guiding experiments and leading to conclusions. Within the realm of science, such hypotheses are crafted after an extensive examination of current knowledge, ensuring their foundation on already established evidence prior to beginning any new inquiry.

Essentially, a hypothesis in the scientific community must present itself as something capable of being tested, this characteristic distinguishes it from mere speculation by allowing its potential verification or falsification through methodical scrutiny. Hypotheses serve as crucial instruments within scientific studies, directing these investigations toward particular queries and forming the backbone upon which all experiments rest in their pursuit for advancements in comprehension.

When formulating a hypothesis for testing within research activities, one should employ language that remains neutral and detached from subjective bias thereby bolstering the legitimacy of outcomes produced during the study. This precision fosters greater confidence in results obtained under rigorous evaluation standards among peers.

Characteristics of a Good Hypothesis

A good hypothesis is the cornerstone of any successful scientific research. It should be clear, concise, and testable, providing a solid foundation for your investigation. Here are some key characteristics that define a good hypothesis:

Clarity : A good hypothesis should be easy to understand and clearly state the expected outcome of the research. For example , “Increased exposure to sunlight will result in taller plant growth” is a clear and straightforward hypothesis.
Conciseness : Avoid unnecessary complexity or jargon. A concise hypothesis is brief and to the point, making it easier to test and analyze. For instance, “Exercise improves mental health” is concise and direct.
Testability : A good hypothesis must be testable and falsifiable, meaning it can be proven or disproven through scientific research methods. For example, “Consuming vitamin C reduces the duration of the common cold” is a testable hypothesis.
Relevance : Ensure your hypothesis is relevant to the research question or problem and aligned with your research objectives. For example, if your research question is about the impact of diet on health, a relevant hypothesis could be “A high-fiber diet reduces the risk of heart disease.”
Specificity : A good hypothesis should be specific and focused on a particular aspect of the research question. For example, “Daily meditation reduces stress levels in college students” is specific and targeted.
Measurability : Your hypothesis should be measurable, meaning it can be quantified or observed. For example, “Regular physical activity lowers blood pressure” is a measurable hypothesis.

By ensuring your hypothesis possesses these characteristics, you set a strong foundation for your scientific research, guiding your investigation towards meaningful and reliable results.

Types of Hypotheses

Scientific research incorporates a range of research hypotheses, which are crucial for proposing relationships between different variables and steering the direction of the investigation. These seven unique forms of hypotheses cater to diverse needs within the realm of scientific inquiry.

Comprehending these various types is essential in selecting an appropriate method for conducting research. To delve into details, we have simple, complex, null and alternative hypotheses. Each brings its distinct features and practical implications to the table. It underscores why recognizing how they diverge and what purposes they serve is fundamental in any scientific study.

Simple Hypothesis

A basic hypothesis suggests a fundamental relationship between two elements: the independent and dependent variable. Take, for example, a hypothesis that says, “The taller growth of plants (dependent variable) is due to increased exposure to sunlight (independent variable).” Such hypotheses are clear-cut and easily testable as they concentrate on one direct cause-and-effect link.

These types of straightforward hypotheses are very beneficial in scientific experiments because they permit the isolation of variables for precise outcome measurement. Their simplicity lends itself well to being an essential component in conducting scientific research, thanks to their unambiguous nature and targeted focus on specific relationships.

Complex Hypothesis

Alternatively, a complex hypothesis proposes an interconnection amongst several variables. It builds on the concept of numerous variable interactions within research parameters. Take for instance a causal hypothesis which asserts that sustained alcohol consumption (the independent variable) leads to liver impairment (the dependent variable), with additional influences like use duration and general health results impacting this relationship.

Involving various factors, complex hypotheses reveal the nuanced interaction of elements that affect results. Although they provide extensive insight into studied phenomena, such hypotheses necessitate advanced research frameworks and analysis techniques to be understood properly.

Null Hypothesis

In the realm of hypothesis testing, the null hypothesis (H0) serves as a fundamental presumption suggesting that there exists no association between the variables under investigation. It posits that variations within the dependent variable are attributed to random chance and not an influential relationship. Take for instance a null hypothesis which could propose “There is no impact of sleep duration on productivity levels.”

The significance of the null hypothesis lies in its role as a reference point which researchers strive to refute during their investigations. Upon uncovering statistical evidence indicative of a substantial linkage, it becomes necessary to discard the null hypothesis. The act of rejecting this foundational assumption is critical for affirming research findings and assessing their importance with respect to outcomes observed.

Alternative Hypothesis

The alternative hypothesis, often represented by H1 or Ha, contradicts the null hypothesis and proposes a meaningful link between variables under examination. For example, where the null hypothesis asserts that a particular medication is ineffective, the alternative might posit that “Compared to placebo treatment, the new drug yields beneficial effects.”

By claiming outcomes are non-random and carry weight, the alternative hypothesis bolsters theoretical assertions. Its testable prediction propels scientific investigation forward as it aims either to corroborate or debunk what’s posited by the null hypothesis.

Consider an assertive statement like “Productivity is influenced by sleep duration” which serves as a crisp articulation of an alternative hypothesis.

Steps to Write a Hypothesis

Crafting a hypothesis is a methodical process that begins with curiosity and culminates in a testable prediction. Writing a hypothesis involves following structured steps to ensure clarity, focus, and researchability. Steps include asking a research question, conducting preliminary research, defining variables, and phrasing the hypothesis as an if-then statement.

Each step is critical in formulating a strong hypothesis to guide research and lead to meaningful discoveries.

Ask a Research Question

A well-defined research question forms the cornerstone of a strong hypothesis, guiding your investigation towards a significant and targeted exploration. By rooting this question in observations and existing studies, it becomes pertinent and ripe for research. For example, noting that certain snacks are more popular could prompt the inquiry: “Does providing healthy snack options in an office setting enhance employee productivity?”.

Such a thoughtfully constructed question lays the groundwork for your research hypothesis, steering your scholarly work to be concentrated and purposeful.

Conduct Preliminary Research

Begin your research endeavor by conducting preliminary investigations into established theories, past studies, and available data. This initial stage is crucial as it equips you with a comprehensive background to craft an informed hypothesis while pinpointing any existing voids in current knowledge. Understanding the concept of a statistical hypothesis can also be beneficial, as it involves drawing conclusions about a population based on a sample and applying statistical evidence.

By reviewing literature and examining previously published research papers, one can discern the various variables of interest and their interconnections. Should the findings from these early inquiries refute your original hypothesis, adjust it accordingly so that it resonates with already recognized evidence.

Define Your Variables

A well-formed hypothesis should unambiguously identify the independent and dependent variables involved. In an investigation exploring how plant growth is affected by sunlight, for instance, plant height represents the dependent variable, while the quantity of sunlight exposure constitutes the independent variable.

It is essential to explicitly state all the variables included in a study so that the hypothesis can be tested with accuracy and specificity. Defining these variables distinctly facilitates a targeted and quantifiable examination.

Phrase as an If-Then Statement

A good hypothesis is typically structured in the form of if-then statements, allowing for a clear demonstration of the anticipated link between different variables. Take, for example, stating that administering drug X could result in reduced fatigue among patients. This outcome would be especially advantageous to individuals receiving cancer therapy. The structure aids in explicitly defining the cause-and-effect dynamic.

In order to craft a strong hypothesis, it should be capable of being tested and grounded on existing knowledge or theoretical frameworks. It should also be framed as a statement that can potentially be refuted by experimental data, which qualifies it as a solidly formulated hypothesis.

Collect Data to Support Your Hypothesis

Once you have formulated a hypothesis, the next crucial step is to collect data to support or refute it. This involves designing and conducting experiments or studies that test the hypothesis, and collecting and analyzing data to determine whether the hypothesis holds true.

Here are the key steps in collecting data to support your hypothesis:

Designing an Experiment or Study : Start by identifying your research question or problem. Design a study or experiment that specifically tests your hypothesis. For example, if your hypothesis is “Daily exercise improves cognitive function,” design an experiment that measures cognitive function in individuals who exercise daily versus those who do not.
Collecting Data : Gather data through various methods such as experiments, surveys, observations, or other techniques. Ensure your data collection methods are reliable and valid. For instance, use standardized tests to measure cognitive function in your exercise study.
Analyzing Data : Use statistical methods or other techniques to analyze the data. This step involves determining whether the data supports or refutes your hypothesis. For example, use statistical tests to compare cognitive function scores between the exercise and non-exercise groups .
Interpreting Results : Interpret the results of your data analysis to determine whether your hypothesis is supported. For instance, if the exercise group shows significantly higher cognitive function scores, your hypothesis is supported. If not, you may need to refine your hypothesis or explore other variables.

By following these steps, you can systematically collect and analyze data to support or refute your hypothesis, ensuring your research is grounded in empirical evidence.

Refining Your Hypothesis

To ensure your hypothesis is precise, comprehensible, verifiable, straightforward, and pertinent, you must refine it meticulously. Creating a compelling hypothesis involves careful consideration of its transparency, purposeful direction and the potential results. This requires unmistakably delineating the subject matter and central point of your experiment.

Your hypothesis should undergo stringent examination to remove any uncertainties and define parameters that guarantee both ethical integrity and scientific credibility. An effective hypothesis not only questions prevailing assumptions, but also maintains an ethically responsible framework.

Testing Your Hypothesis

Having a robust research methodology is essential for efficiently evaluating your hypothesis. It is important to ensure that the integrity and validity of the research are upheld through adherence to ethical standards. The data gathered ought to be both representative and tailored specifically towards validating or invalidating the hypothesis.

In order to ascertain whether there’s any significant difference, statistical analyses measure variations both within and across groups. Frequently, the decision on whether to discard the null hypothesis hinges on establishing a p-value cut-off point, which conventionally stands at 0.05.

Tips for Writing a Research Hypothesis

Writing a research hypothesis can be a challenging task, but with the right approach, you can craft a strong and testable hypothesis. Here are some tips to help you write a research hypothesis:

Start with a Research Question : A good hypothesis starts with a clear and focused research question. For example, “Does regular exercise improve mental health?” can lead to a hypothesis like “Regular exercise reduces symptoms of depression.”
Conduct Preliminary Research : Conducting preliminary research helps you identify a knowledge gap in your field and develop a hypothesis that is relevant and testable. Review existing literature and studies to inform your hypothesis.
Use Clear and Concise Language : A good hypothesis should be easy to understand and use clear and concise language. Avoid jargon and complex terms. For example, “Increased screen time negatively impacts sleep quality” is clear and straightforward.
Avoid Ambiguity and Vagueness : Ensure your hypothesis is free from ambiguity and vagueness. Clearly state the expected outcome of the research. For example, “Consuming caffeine before bedtime reduces sleep duration” is specific and unambiguous.
Make Sure It Is Testable : A good hypothesis should be testable and falsifiable, meaning it can be proven or disproven through scientific research methods. For example, “A high-protein diet increases muscle mass” is a testable hypothesis.
Use Existing Knowledge and Research : Base your hypothesis on existing knowledge and research. Align it with your research objectives and ensure it is grounded in established theories or findings.

Common mistakes to avoid when writing a research hypothesis include:

Making It Too Broad or Too Narrow : A good hypothesis should be specific and focused on a particular aspect of the research question. Avoid overly broad or narrow hypotheses.
Making It Too Vague or Ambiguous : Ensure your hypothesis is clear and concise, avoiding ambiguity and vagueness.
Failing to Make It Testable : A good hypothesis should be testable and falsifiable. Ensure it can be proven or disproven through scientific research methods.
Failing to Use Existing Knowledge and Research : Base your hypothesis on existing knowledge and research. Align it with your research objectives and ensure it is grounded in established theories or findings.

By following these tips and avoiding common mistakes, you can write a strong and testable research hypothesis that will guide your scientific investigation towards meaningful and reliable results.

Examples of Good and Bad Hypotheses

A well-constructed hypothesis is distinct, precise, and capable of being empirically verified. To be considered a good hypothesis, it must offer measurable and examinable criteria through experimental means. Take the claim “Working from home boosts job satisfaction” as an example. This posits a testable outcome related to work environments.

On the other hand, a subpar hypothesis such as “Garlic repels vampires” falls short because it hinges on fantastical elements that cannot be substantiated or refuted in reality. The ability to distinguish between strong and weak hypotheses plays an essential role in conducting successful research.

Importance of a Testable Hypothesis

A hypothesis that can be subjected to testing forms the basis of a scientific experiment, outlining anticipated results. For a hypothesis to qualify as testable, it must possess key attributes such as being able to be falsified and verifiable or disprovable via experimental means. It serves as an essential platform for conducting fresh research with the potential to confirm or debunk it.

Crafting a robust testable hypothesis yields clear forecasts derived from previous studies. Should both the predictions and outcomes stemming from a hypothesis lack this critical aspect of testability, they will remain ambiguous, rendering the associated experiment ineffective in conclusively proving or negating anything of substance.

In summary, crafting a strong hypothesis constitutes an essential ability within the realm of scientific research. Grasping the various forms of hypotheses and mastering the process for their formulation and refinement are critical to establishing your research as solid and significant. It is crucial to underscore that having a testable hypothesis serves as the bedrock for successful scientific investigation.

Frequently Asked Questions

How can you formulate a hypothesis.

To formulate a hypothesis, first state the question your experiment aims to answer and identify the independent and dependent variables.

Then create an “If, Then” statement that succinctly defines the relationship between these variables.

What is a hypothesis in scientific research?

In the research process, a hypothesis acts as a tentative concept that is put forward for additional scrutiny and examination, establishing the bedrock upon which scientific experiments are built. It steers the course of research by forecasting possible results.

What are the different types of hypotheses?

Hypotheses can be classified into simple, complex, null, and alternative types, each type fulfilling distinct roles in scientific research.

Understanding these differences is crucial for effective hypothesis formulation.

How do I write a hypothesis?

To write a hypothesis, start by formulating a research question and conducting preliminary research.

Then define your variables and express your hypothesis in the form of an if-then statement.

Why is a testable hypothesis important?

Having a testable hypothesis is vital because it provides a definitive structure for conducting research, allowing for particular predictions that experimentation can either verify or refute.

Such an element significantly improves the process of scientific investigation.

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How to Write a Hypothesis in 6 Steps, With Examples

A hypothesis is a statement that explains the predictions and reasoning of your research—an “educated guess” about how your scientific experiments will end. As a fundamental part of the scientific method, a good hypothesis is carefully written, but even the simplest ones can be difficult to put into words.

Want to know how to write a hypothesis for your academic paper ? Below we explain the different types of hypotheses, what a good hypothesis requires, the steps to write your own, and plenty of examples.

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What is a hypothesis?

One of our 10 essential words for university success , a hypothesis is one of the earliest stages of the scientific method. It’s essentially an educated guess—based on observations—of what the results of your experiment or research will be.

Some hypothesis examples include:

If I water plants daily they will grow faster.
Adults can more accurately guess the temperature than children can.
Butterflies prefer white flowers to orange ones.

If you’ve noticed that watering your plants every day makes them grow faster, your hypothesis might be “plants grow better with regular watering.” From there, you can begin experiments to test your hypothesis; in this example, you might set aside two plants, water one but not the other, and then record the results to see the differences.

The language of hypotheses always discusses variables , or the elements that you’re testing. Variables can be objects, events, concepts, etc.—whatever is observable.

There are two types of variables: independent and dependent. Independent variables are the ones that you change for your experiment, whereas dependent variables are the ones that you can only observe. In the above example, our independent variable is how often we water the plants and the dependent variable is how well they grow.

Hypotheses determine the direction and organization of your subsequent research methods, and that makes them a big part of writing a research paper . Ultimately the reader wants to know whether your hypothesis was proven true or false, so it must be written clearly in the introduction and/or abstract of your paper.

7 examples of hypotheses

Depending on the nature of your research and what you expect to find, your hypothesis will fall into one or more of the seven main categories. Keep in mind that these categories are not exclusive, so the same hypothesis might qualify as several different types.

1 Simple hypothesis

A simple hypothesis suggests only the relationship between two variables: one independent and one dependent.

If you stay up late, then you feel tired the next day.
Turning off your phone makes it charge faster.

2 Complex hypothesis

A complex hypothesis suggests the relationship between more than two variables, for example, two independents and one dependent, or vice versa.

People who both (1) eat a lot of fatty foods and (2) have a family history of health problems are more likely to develop heart diseases.
Older people who live in rural areas are happier than younger people who live in rural areas.

3 Null hypothesis

A null hypothesis, abbreviated as H 0 , suggests that there is no relationship between variables.

There is no difference in plant growth when using either bottled water or tap water.
Professional psychics do not win the lottery more than other people.

4 Alternative hypothesis

An alternative hypothesis, abbreviated as H 1 or H A , is used in conjunction with a null hypothesis. It states the opposite of the null hypothesis, so that one and only one must be true.

Plants grow better with bottled water than tap water.
Professional psychics win the lottery more than other people.

5 Logical hypothesis

A logical hypothesis suggests a relationship between variables without actual evidence. Claims are instead based on reasoning or deduction, but lack actual data.

An alien raised on Venus would have trouble breathing in Earth’s atmosphere.
Dinosaurs with sharp, pointed teeth were probably carnivores.

6 Empirical hypothesis

An empirical hypothesis, also known as a “working hypothesis,” is one that is currently being tested. Unlike logical hypotheses, empirical hypotheses rely on concrete data.

Customers at restaurants will tip the same even if the wait staff’s base salary is raised.
Washing your hands every hour can reduce the frequency of illness.

7 Statistical hypothesis

A statistical hypothesis is when you test only a sample of a population and then apply statistical evidence to the results to draw a conclusion about the entire population. Instead of testing everything , you test only a portion and generalize the rest based on preexisting data.

In humans, the birth-gender ratio of males to females is 1.05 to 1.00.
Approximately 2% of the world population has natural red hair.

What makes a good hypothesis?

No matter what you’re testing, a good hypothesis is written according to the same guidelines. In particular, keep these five characteristics in mind:

Cause and effect

Hypotheses always include a cause-and-effect relationship where one variable causes another to change (or not change if you’re using a null hypothesis). This can best be reflected as an if-then statement: If one variable occurs, then another variable changes.

Testable prediction

Most hypotheses are designed to be tested (with the exception of logical hypotheses). Before committing to a hypothesis, make sure you’re actually able to conduct experiments on it. Choose a testable hypothesis with an independent variable that you have absolute control over.

Independent and dependent variables

Define your variables in your hypothesis so your readers understand the big picture. You don’t have to specifically say which ones are independent and dependent variables, but you definitely want to mention them all.

Candid language

Writing can easily get convoluted, so make sure your hypothesis remains as simple and clear as possible. Readers use your hypothesis as a contextual pillar to unify your entire paper, so there should be no confusion or ambiguity. If you’re unsure about your phrasing, try reading your hypothesis to a friend to see if they understand.

Adherence to ethics

It’s not always about what you can test, but what you should test. Avoid hypotheses that require questionable or taboo experiments to keep ethics (and therefore, credibility) intact.

How to write a hypothesis in 6 steps

1 ask a question.

Curiosity has inspired some of history’s greatest scientific achievements, so a good place to start is to ask yourself questions about the world around you. Why are things the way they are? What causes the factors you see around you? If you can, choose a research topic that you’re interested in so your curiosity comes naturally.

2 Conduct preliminary research

Next, collect some background information on your topic. How much background information you need depends on what you’re attempting. It could require reading several books, or it could be as simple as performing a web search for a quick answer. You don’t necessarily have to prove or disprove your hypothesis at this stage; rather, collect only what you need to prove or disprove it yourself.

3 Define your variables

Once you have an idea of what your hypothesis will be, select which variables are independent and which are dependent. Remember that independent variables can only be factors that you have absolute control over, so consider the limits of your experiment before finalizing your hypothesis.

4 Phrase it as an if-then statement

When writing a hypothesis, it helps to phrase it using an if-then format, such as, “ If I water a plant every day, then it will grow better.” This format can get tricky when dealing with multiple variables, but in general, it’s a reliable method for expressing the cause-and-effect relationship you’re testing.

5 Collect data to support your hypothesis

A hypothesis is merely a means to an end. The priority of any scientific research is the conclusion. Once you have your hypothesis laid out and your variables chosen, you can then begin your experiments. Ideally, you’ll collect data to support your hypothesis, but don’t worry if your research ends up proving it wrong—that’s all part of the scientific method.

6 Write with confidence

Last, you’ll want to record your findings in a research paper for others to see. This requires a bit of writing know-how, quite a different skill set than conducting experiments.

That’s where Grammarly can be a major help; our writing suggestions point out not only grammar and spelling mistakes , but also new word choices and better phrasing. While you write, Grammarly automatically recommends optimal language and highlights areas where readers might get confused, ensuring that your hypothesis—and your final paper—are clear and polished.

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Scientific Hypotheses: Writing, Promoting, and Predicting Implications

Armen yuri gasparyan, lilit ayvazyan, ulzhan mukanova, marlen yessirkepov, george d kitas.

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Address for Correspondence: Armen Yuri Gasparyan, MD. Departments of Rheumatology and Research and Development, Dudley Group NHS Foundation Trust (Teaching Trust of the University of Birmingham, UK), Russells Hall Hospital, Pensnett Road, Dudley, West Midlands DY1 2HQ, UK. [email protected]

Corresponding author.

Received 2019 Sep 2; Accepted 2019 Oct 28; Collection date 2019 Nov 25.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( https://creativecommons.org/licenses/by-nc/4.0/ ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Scientific hypotheses are essential for progress in rapidly developing academic disciplines. Proposing new ideas and hypotheses require thorough analyses of evidence-based data and predictions of the implications. One of the main concerns relates to the ethical implications of the generated hypotheses. The authors may need to outline potential benefits and limitations of their suggestions and target widely visible publication outlets to ignite discussion by experts and start testing the hypotheses. Not many publication outlets are currently welcoming hypotheses and unconventional ideas that may open gates to criticism and conservative remarks. A few scholarly journals guide the authors on how to structure hypotheses. Reflecting on general and specific issues around the subject matter is often recommended for drafting a well-structured hypothesis article. An analysis of influential hypotheses, presented in this article, particularly Strachan's hygiene hypothesis with global implications in the field of immunology and allergy, points to the need for properly interpreting and testing new suggestions. Envisaging the ethical implications of the hypotheses should be considered both by authors and journal editors during the writing and publishing process.

Keywords: Bibliographic Databases, Peer Review, Writing, Research Ethics, Hypothesis, Impact

INTRODUCTION

We live in times of digitization that radically changes scientific research, reporting, and publishing strategies. Researchers all over the world are overwhelmed with processing large volumes of information and searching through numerous online platforms, all of which make the whole process of scholarly analysis and synthesis complex and sophisticated.

Current research activities are diversifying to combine scientific observations with analysis of facts recorded by scholars from various professional backgrounds. 1 Citation analyses and networking on social media are also becoming essential for shaping research and publishing strategies globally. 2 Learning specifics of increasingly interdisciplinary research studies and acquiring information facilitation skills aid researchers in formulating innovative ideas and predicting developments in interrelated scientific fields.

Arguably, researchers are currently offered more opportunities than in the past for generating new ideas by performing their routine laboratory activities, observing individual cases and unusual developments, and critically analyzing published scientific facts. What they need at the start of their research is to formulate a scientific hypothesis that revisits conventional theories, real-world processes, and related evidence to propose new studies and test ideas in an ethical way. 3 Such a hypothesis can be of most benefit if published in an ethical journal with wide visibility and exposure to relevant online databases and promotion platforms.

Although hypotheses are crucially important for the scientific progress, only few highly skilled researchers formulate and eventually publish their innovative ideas per se . Understandably, in an increasingly competitive research environment, most authors would prefer to prioritize their ideas by discussing and conducting tests in their own laboratories or clinical departments, and publishing research reports afterwards. However, there are instances when simple observations and research studies in a single center are not capable of explaining and testing new groundbreaking ideas. Formulating hypothesis articles first and calling for multicenter and interdisciplinary research can be a solution in such instances, potentially launching influential scientific directions, if not academic disciplines.

The aim of this article is to overview the importance and implications of infrequently published scientific hypotheses that may open new avenues of thinking and research.

Despite the seemingly established views on innovative ideas and hypotheses as essential research tools, no structured definition exists to tag the term and systematically track related articles. In 1973, the Medical Subject Heading (MeSH) of the U.S. National Library of Medicine introduced “Research Design” as a structured keyword that referred to the importance of collecting data and properly testing hypotheses, and indirectly linked the term to ethics, methods and standards, among many other subheadings.

One of the experts in the field defines “hypothesis” as a well-argued analysis of available evidence to provide a realistic (scientific) explanation of existing facts, fill gaps in public understanding of sophisticated processes, and propose a new theory or a test. 4 A hypothesis can be proven wrong partially or entirely. However, even such an erroneous hypothesis may influence progress in science by initiating professional debates that help generate more realistic ideas. The main ethical requirement for hypothesis authors is to be honest about the limitations of their suggestions. 5

EXAMPLES OF INFLUENTIAL SCIENTIFIC HYPOTHESES

Daily routine in a research laboratory may lead to groundbreaking discoveries provided the daily accounts are comprehensively analyzed and reproduced by peers. The discovery of penicillin by Sir Alexander Fleming (1928) can be viewed as a prime example of such discoveries that introduced therapies to treat staphylococcal and streptococcal infections and modulate blood coagulation. 6 , 7 Penicillin got worldwide recognition due to the inventor's seminal works published by highly prestigious and widely visible British journals, effective ‘real-world’ antibiotic therapy of pneumonia and wounds during World War II, and euphoric media coverage. 8 In 1945, Fleming, Florey and Chain got a much deserved Nobel Prize in Physiology or Medicine for the discovery that led to the mass production of the wonder drug in the U.S. and ‘real-world practice’ that tested the use of penicillin. What remained globally unnoticed is that Zinaida Yermolyeva, the outstanding Soviet microbiologist, created the Soviet penicillin, which turned out to be more effective than the Anglo-American penicillin and entered mass production in 1943; that year marked the turning of the tide of the Great Patriotic War. 9 One of the reasons of the widely unnoticed discovery of Zinaida Yermolyeva is that her works were published exclusively by local Russian (Soviet) journals.

The past decades have been marked by an unprecedented growth of multicenter and global research studies involving hundreds and thousands of human subjects. This trend is shaped by an increasing number of reports on clinical trials and large cohort studies that create a strong evidence base for practice recommendations. Mega-studies may help generate and test large-scale hypotheses aiming to solve health issues globally. Properly designed epidemiological studies, for example, may introduce clarity to the hygiene hypothesis that was originally proposed by David Strachan in 1989. 10 David Strachan studied the epidemiology of hay fever in a cohort of 17,414 British children and concluded that declining family size and improved personal hygiene had reduced the chances of cross infections in families, resulting in epidemics of atopic disease in post-industrial Britain. Over the past four decades, several related hypotheses have been proposed to expand the potential role of symbiotic microorganisms and parasites in the development of human physiological immune responses early in life and protection from allergic and autoimmune diseases later on. 11 , 12 Given the popularity and the scientific importance of the hygiene hypothesis, it was introduced as a MeSH term in 2012. 13

Hypotheses can be proposed based on an analysis of recorded historic events that resulted in mass migrations and spreading of certain genetic diseases. As a prime example, familial Mediterranean fever (FMF), the prototype periodic fever syndrome, is believed to spread from Mesopotamia to the Mediterranean region and all over Europe due to migrations and religious prosecutions millennia ago. 14 Genetic mutations spearing mild clinical forms of FMF are hypothesized to emerge and persist in the Mediterranean region as protective factors against more serious infectious diseases, particularly tuberculosis, historically common in that part of the world. 15 The speculations over the advantages of carrying the MEditerranean FeVer (MEFV) gene are further strengthened by recorded low mortality rates from tuberculosis among FMF patients of different nationalities living in Tunisia in the first half of the 20th century. 16

Diagnostic hypotheses shedding light on peculiarities of diseases throughout the history of mankind can be formulated using artefacts, particularly historic paintings. 17 Such paintings may reveal joint deformities and disfigurements due to rheumatic diseases in individual subjects. A series of paintings with similar signs of pathological conditions interpreted in a historic context may uncover mysteries of epidemics of certain diseases, which is the case with Ruben's paintings depicting signs of rheumatic hands and making some doctors to believe that rheumatoid arthritis was common in Europe in the 16th and 17th century. 18

WRITING SCIENTIFIC HYPOTHESES

There are author instructions of a few journals that specifically guide how to structure, format, and make submissions categorized as hypotheses attractive. One of the examples is presented by Med Hypotheses , the flagship journal in its field with more than four decades of publishing and influencing hypothesis authors globally. However, such guidance is not based on widely discussed, implemented, and approved reporting standards, which are becoming mandatory for all scholarly journals.

Generating new ideas and scientific hypotheses is a sophisticated task since not all researchers and authors are skilled to plan, conduct, and interpret various research studies. Some experience with formulating focused research questions and strong working hypotheses of original research studies is definitely helpful for advancing critical appraisal skills. However, aspiring authors of scientific hypotheses may need something different, which is more related to discerning scientific facts, pooling homogenous data from primary research works, and synthesizing new information in a systematic way by analyzing similar sets of articles. To some extent, this activity is reminiscent of writing narrative and systematic reviews. As in the case of reviews, scientific hypotheses need to be formulated on the basis of comprehensive search strategies to retrieve all available studies on the topics of interest and then synthesize new information selectively referring to the most relevant items. One of the main differences between scientific hypothesis and review articles relates to the volume of supportive literature sources ( Table 1 ). In fact, hypothesis is usually formulated by referring to a few scientific facts or compelling evidence derived from a handful of literature sources. 19 By contrast, reviews require analyses of a large number of published documents retrieved from several well-organized and evidence-based databases in accordance with predefined search strategies. 20 , 21 , 22

Table 1. Characteristics of scientific hypotheses and narrative and systematic reviews.

The format of hypotheses, especially the implications part, may vary widely across disciplines. Clinicians may limit their suggestions to the clinical manifestations of diseases, outcomes, and management strategies. Basic and laboratory scientists analysing genetic, molecular, and biochemical mechanisms may need to view beyond the frames of their narrow fields and predict social and population-based implications of the proposed ideas. 23

Advanced writing skills are essential for presenting an interesting theoretical article which appeals to the global readership. Merely listing opposing facts and ideas, without proper interpretation and analysis, may distract the experienced readers. The essence of a great hypothesis is a story behind the scientific facts and evidence-based data.

ETHICAL IMPLICATIONS

The authors of hypotheses substantiate their arguments by referring to and discerning rational points from published articles that might be overlooked by others. Their arguments may contradict the established theories and practices, and pose global ethical issues, particularly when more or less efficient medical technologies and public health interventions are devalued. The ethical issues may arise primarily because of the careless references to articles with low priorities, inadequate and apparently unethical methodologies, and concealed reporting of negative results. 24 , 25

Misinterpretation and misunderstanding of the published ideas and scientific hypotheses may complicate the issue further. For example, Alexander Fleming, whose innovative ideas of penicillin use to kill susceptible bacteria saved millions of lives, warned of the consequences of uncontrolled prescription of the drug. The issue of antibiotic resistance had emerged within the first ten years of penicillin use on a global scale due to the overprescription that affected the efficacy of antibiotic therapies, with undesirable consequences for millions. 26

The misunderstanding of the hygiene hypothesis that primarily aimed to shed light on the role of the microbiome in allergic and autoimmune diseases resulted in decline of public confidence in hygiene with dire societal implications, forcing some experts to abandon the original idea. 27 , 28 Although that hypothesis is unrelated to the issue of vaccinations, the public misunderstanding has resulted in decline of vaccinations at a time of upsurge of old and new infections.

A number of ethical issues are posed by the denial of the viral (human immunodeficiency viruses; HIV) hypothesis of acquired Immune deficiency Syndrome (AIDS) by Peter Duesberg, who overviewed the links between illicit recreational drugs and antiretroviral therapies with AIDS and refuted the etiological role of HIV. 29 That controversial hypothesis was rejected by several journals, but was eventually published without external peer review at Med Hypotheses in 2010. The publication itself raised concerns of the unconventional editorial policy of the journal, causing major perturbations and more scrutinized publishing policies by journals processing hypotheses.

WHERE TO PUBLISH HYPOTHESES

Although scientific authors are currently well informed and equipped with search tools to draft evidence-based hypotheses, there are still limited quality publication outlets calling for related articles. The journal editors may be hesitant to publish articles that do not adhere to any research reporting guidelines and open gates for harsh criticism of unconventional and untested ideas. Occasionally, the editors opting for open-access publishing and upgrading their ethics regulations launch a section to selectively publish scientific hypotheses attractive to the experienced readers. 30 However, the absence of approved standards for this article type, particularly no mandate for outlining potential ethical implications, may lead to publication of potentially harmful ideas in an attractive format.

A suggestion of simultaneously publishing multiple or alternative hypotheses to balance the reader views and feedback is a potential solution for the mainstream scholarly journals. 31 However, that option alone is hardly applicable to emerging journals with unconventional quality checks and peer review, accumulating papers with multiple rejections by established journals.

A large group of experts view hypotheses with improbable and controversial ideas publishable after formal editorial (in-house) checks to preserve the authors' genuine ideas and avoid conservative amendments imposed by external peer reviewers. 32 That approach may be acceptable for established publishers with large teams of experienced editors. However, the same approach can lead to dire consequences if employed by nonselective start-up, open-access journals processing all types of articles and primarily accepting those with charged publication fees. 33 In fact, pseudoscientific ideas arguing Newton's and Einstein's seminal works or those denying climate change that are hardly testable have already found their niche in substandard electronic journals with soft or nonexistent peer review. 34

CITATIONS AND SOCIAL MEDIA ATTENTION

The available preliminary evidence points to the attractiveness of hypothesis articles for readers, particularly those from research-intensive countries who actively download related documents. 35 However, citations of such articles are disproportionately low. Only a small proportion of top-downloaded hypotheses (13%) in the highly prestigious Med Hypotheses receive on average 5 citations per article within a two-year window. 36

With the exception of a few historic papers, the vast majority of hypotheses attract relatively small number of citations in a long term. 36 Plausible explanations are that these articles often contain a single or only a few citable points and that suggested research studies to test hypotheses are rarely conducted and reported, limiting chances of citing and crediting authors of genuine research ideas.

A snapshot analysis of citation activity of hypothesis articles may reveal interest of the global scientific community towards their implications across various disciplines and countries. As a prime example, Strachan's hygiene hypothesis, published in 1989, 10 is still attracting numerous citations on Scopus, the largest bibliographic database. As of August 28, 2019, the number of the linked citations in the database is 3,201. Of the citing articles, 160 are cited at least 160 times ( h -index of this research topic = 160). The first three citations are recorded in 1992 and followed by a rapid annual increase in citation activity and a peak of 212 in 2015 ( Fig. 1 ). The top 5 sources of the citations are Clin Exp Allergy (n = 136), J Allergy Clin Immunol (n = 119), Allergy (n = 81), Pediatr Allergy Immunol (n = 69), and PLOS One (n = 44). The top 5 citing authors are leading experts in pediatrics and allergology Erika von Mutius (Munich, Germany, number of publications with the index citation = 30), Erika Isolauri (Turku, Finland, n = 27), Patrick G Holt (Subiaco, Australia, n = 25), David P. Strachan (London, UK, n = 23), and Bengt Björksten (Stockholm, Sweden, n = 22). The U.S. is the leading country in terms of citation activity with 809 related documents, followed by the UK (n = 494), Germany (n = 314), Australia (n = 211), and the Netherlands (n = 177). The largest proportion of citing documents are articles (n = 1,726, 54%), followed by reviews (n = 950, 29.7%), and book chapters (n = 213, 6.7%). The main subject areas of the citing items are medicine (n = 2,581, 51.7%), immunology and microbiology (n = 1,179, 23.6%), and biochemistry, genetics and molecular biology (n = 415, 8.3%).

Fig. 1. Number of Scopus-indexed items citing Strachan's hygiene hypothesis in 1992–2019 (as of August 28, 2019).

Interestingly, a recent analysis of 111 publications related to Strachan's hygiene hypothesis, stating that the lack of exposure to infections in early life increases the risk of rhinitis, revealed a selection bias of 5,551 citations on Web of Science. 37 The articles supportive of the hypothesis were cited more than nonsupportive ones (odds ratio adjusted for study design, 2.2; 95% confidence interval, 1.6–3.1). A similar conclusion pointing to a citation bias distorting bibliometrics of hypotheses was reached by an earlier analysis of a citation network linked to the idea that β-amyloid, which is involved in the pathogenesis of Alzheimer disease, is produced by skeletal muscle of patients with inclusion body myositis. 38 The results of both studies are in line with the notion that ‘positive’ citations are more frequent in the field of biomedicine than ‘negative’ ones, and that citations to articles with proven hypotheses are too common. 39

Social media channels are playing an increasingly active role in the generation and evaluation of scientific hypotheses. In fact, publicly discussing research questions on platforms of news outlets, such as Reddit, may shape hypotheses on health-related issues of global importance, such as obesity. 40 Analyzing Twitter comments, researchers may reveal both potentially valuable ideas and unfounded claims that surround groundbreaking research ideas. 41 Social media activities, however, are unevenly distributed across different research topics, journals and countries, and these are not always objective professional reflections of the breakthroughs in science. 2 , 42

Scientific hypotheses are essential for progress in science and advances in healthcare. Innovative ideas should be based on a critical overview of related scientific facts and evidence-based data, often overlooked by others. To generate realistic hypothetical theories, the authors should comprehensively analyze the literature and suggest relevant and ethically sound design for future studies. They should also consider their hypotheses in the context of research and publication ethics norms acceptable for their target journals. The journal editors aiming to diversify their portfolio by maintaining and introducing hypotheses section are in a position to upgrade guidelines for related articles by pointing to general and specific analyses of the subject, preferred study designs to test hypotheses, and ethical implications. The latter is closely related to specifics of hypotheses. For example, editorial recommendations to outline benefits and risks of a new laboratory test or therapy may result in a more balanced article and minimize associated risks afterwards.

Not all scientific hypotheses have immediate positive effects. Some, if not most, are never tested in properly designed research studies and never cited in credible and indexed publication outlets. Hypotheses in specialized scientific fields, particularly those hardly understandable for nonexperts, lose their attractiveness for increasingly interdisciplinary audience. The authors' honest analysis of the benefits and limitations of their hypotheses and concerted efforts of all stakeholders in science communication to initiate public discussion on widely visible platforms and social media may reveal rational points and caveats of the new ideas.

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

Conceptualization: Gasparyan AY, Yessirkepov M, Kitas GD.
Methodology: Gasparyan AY, Mukanova U, Ayvazyan L.
Writing - original draft: Gasparyan AY, Ayvazyan L, Yessirkepov M.
Writing - review & editing: Gasparyan AY, Yessirkepov M, Mukanova U, Kitas GD.
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What is a Hypothesis – Types, Examples and Writing Guide

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In research, a hypothesis is a clear, testable statement predicting the relationship between variables or the outcome of a study. Hypotheses form the foundation of scientific inquiry, providing a direction for investigation and guiding the data collection and analysis process. Hypotheses are typically used in quantitative research but can also inform some qualitative studies by offering a preliminary assumption about the subject being explored.

A hypothesis is a specific, testable prediction or statement that suggests an expected relationship between variables in a study. It acts as a starting point, guiding researchers to examine whether their predictions hold true based on collected data. For a hypothesis to be useful, it must be clear, concise, and based on prior knowledge or theoretical frameworks.

Key Characteristics of a Hypothesis :

Testable : Must be possible to evaluate or observe the outcome through experimentation or analysis.
Specific : Clearly defines variables and the expected relationship or outcome.
Predictive : States an anticipated effect or association that can be confirmed or refuted.

Example : “Increasing the amount of daily physical exercise will lead to a reduction in stress levels among college students.”

Types of Hypotheses

Hypotheses can be categorized into several types, depending on their structure, purpose, and the type of relationship they suggest. The most common types include null hypothesis , alternative hypothesis , directional hypothesis , and non-directional hypothesis .

1. Null Hypothesis (H₀)

Definition : The null hypothesis states that there is no relationship between the variables being studied or that any observed effect is due to chance. It serves as the default position, which researchers aim to test against to determine if a significant effect or association exists.

Purpose : To provide a baseline that can be statistically tested to verify if a relationship or difference exists.

Example : “There is no difference in academic performance between students who receive additional tutoring and those who do not.”

2. Alternative Hypothesis (H₁ or Hₐ)

Definition : The alternative hypothesis proposes that there is a relationship or effect between variables. This hypothesis contradicts the null hypothesis and suggests that any observed result is not due to chance.

Purpose : To present an expected outcome that researchers aim to support with data.

Example : “Students who receive additional tutoring will perform better academically than those who do not.”

3. Directional Hypothesis

Definition : A directional hypothesis specifies the direction of the expected relationship between variables, predicting either an increase, decrease, positive, or negative effect.

Purpose : To provide a more precise prediction by indicating the expected direction of the relationship.

Example : “Increasing the duration of daily exercise will lead to a decrease in stress levels among adults.”

4. Non-Directional Hypothesis

Definition : A non-directional hypothesis states that there is a relationship between variables but does not specify the direction of the effect.

Purpose : To allow for exploration of the relationship without committing to a particular direction.

Example : “There is a difference in stress levels between adults who exercise regularly and those who do not.”

Examples of Hypotheses in Different Fields

Null Hypothesis : “There is no difference in anxiety levels between individuals who practice mindfulness and those who do not.”
Alternative Hypothesis : “Individuals who practice mindfulness will report lower anxiety levels than those who do not.”
Directional Hypothesis : “Providing feedback will improve students’ motivation to learn.”
Non-Directional Hypothesis : “There is a difference in motivation levels between students who receive feedback and those who do not.”
Null Hypothesis : “There is no association between diet and energy levels among teenagers.”
Alternative Hypothesis : “A balanced diet is associated with higher energy levels among teenagers.”
Directional Hypothesis : “An increase in employee engagement activities will lead to improved job satisfaction.”
Non-Directional Hypothesis : “There is a relationship between employee engagement activities and job satisfaction.”
Null Hypothesis : “The introduction of green spaces does not affect urban air quality.”
Alternative Hypothesis : “Green spaces improve urban air quality.”

Writing Guide for Hypotheses

Writing a clear, testable hypothesis involves several steps, starting with understanding the research question and selecting variables. Here’s a step-by-step guide to writing an effective hypothesis.

Step 1: Identify the Research Question

Start by defining the primary research question you aim to investigate. This question should be focused, researchable, and specific enough to allow for hypothesis formation.

Example : “Does regular physical exercise improve mental well-being in college students?”

Step 2: Conduct Background Research

Review relevant literature to gain insight into existing theories, studies, and gaps in knowledge. This helps you understand prior findings and guides you in forming a logical hypothesis based on evidence.

Example : Research shows a positive correlation between exercise and mental well-being, which supports forming a hypothesis in this area.

Step 3: Define the Variables

Identify the independent and dependent variables. The independent variable is the factor you manipulate or consider as the cause, while the dependent variable is the outcome or effect you are measuring.

Independent Variable : Amount of physical exercise
Dependent Variable : Mental well-being (measured through self-reported stress levels)

Step 4: Choose the Hypothesis Type

Select the hypothesis type based on the research question. If you predict a specific outcome or direction, use a directional hypothesis. If not, a non-directional hypothesis may be suitable.

Example : “Increasing the frequency of physical exercise will reduce stress levels among college students” (directional hypothesis).

Step 5: Write the Hypothesis

Formulate the hypothesis as a clear, concise statement. Ensure it is specific, testable, and focuses on the relationship between the variables.

Example : “College students who exercise at least three times per week will report lower stress levels than those who do not exercise regularly.”

Step 6: Test and Refine (Optional)

In some cases, it may be necessary to refine the hypothesis after conducting a preliminary test or pilot study. This ensures that your hypothesis is realistic and feasible within the study parameters.

Tips for Writing an Effective Hypothesis

Use Clear Language : Avoid jargon or ambiguous terms to ensure your hypothesis is easily understandable.
Be Specific : Specify the expected relationship between the variables, and, if possible, include the direction of the effect.
Ensure Testability : Frame the hypothesis in a way that allows for empirical testing or observation.
Focus on One Relationship : Avoid complexity by focusing on a single, clear relationship between variables.
Make It Measurable : Choose variables that can be quantified or observed to simplify data collection and analysis.

Common Mistakes to Avoid

Vague Statements : Avoid vague hypotheses that don’t specify a clear relationship or outcome.
Unmeasurable Variables : Ensure that the variables in your hypothesis can be observed, measured, or quantified.
Overly Complex Hypotheses : Keep the hypothesis simple and focused, especially for beginner researchers.
Using Personal Opinions : Avoid subjective or biased language that could impact the neutrality of the hypothesis.

Examples of Well-Written Hypotheses

Psychology : “Adolescents who spend more than two hours on social media per day will report higher levels of anxiety than those who spend less than one hour.”
Business : “Increasing customer service training will improve customer satisfaction ratings among retail employees.”
Health : “Consuming a diet rich in fruits and vegetables is associated with lower cholesterol levels in adults.”
Education : “Students who participate in active learning techniques will have higher retention rates compared to those in traditional lecture-based classrooms.”
Environmental Science : “Urban areas with more green spaces will report lower average temperatures than those with minimal green coverage.”

A well-formulated hypothesis is essential to the research process, providing a clear and testable prediction about the relationship between variables. Understanding the different types of hypotheses, following a structured writing approach, and avoiding common pitfalls help researchers create hypotheses that effectively guide data collection, analysis, and conclusions. Whether working in psychology, education, health sciences, or any other field, an effective hypothesis sharpens the focus of a study and enhances the rigor of research.

Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.). SAGE Publications.
Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed.). SAGE Publications.
Trochim, W. M. K. (2006). The Research Methods Knowledge Base (3rd ed.). Atomic Dog Publishing.
McLeod, S. A. (2019). What is a Hypothesis? Retrieved from https://www.simplypsychology.org/what-is-a-hypotheses.html
Walliman, N. (2017). Research Methods: The Basics (2nd ed.). Routledge.

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Understanding Hypotheses in Scientific Research

In the world of scientific research, the term “hypothesis” holds a central and foundational role. It serves as the starting point for inquiry, offering a proposed explanation for a phenomenon that has yet to be fully understood. Without a clear hypothesis, scientific research would lack direction, becoming a chaotic collection of unrelated observations. This blog delves into the essential concept of a hypothesis, breaking down its definition, purpose, and role within the broader scientific method. Whether you’re just beginning to explore research methodology or looking to refine your understanding, this post will provide an accessible and comprehensive look at hypotheses in scientific research.

What is a Hypothesis?
The Role of Hypotheses in Scientific Research
Characteristics of a Good Hypothesis
How Hypotheses Drive Scientific Progress
Testing the Hypothesis: Experimentation and Observation
Null and Alternative Hypotheses
Types of Hypotheses
Descriptive Hypothesis
Relational Hypothesis
Causal Hypothesis
Formulating a Hypothesis: A Step-by-Step Guide
Why Hypotheses Are Essential to Scientific Discovery
Real-World Example: The Hypothesis that Changed the World

What is a Hypothesis? 🔗

A hypothesis is essentially a testable statement or educated guess about the relationship between two or more variables. It predicts an outcome based on prior knowledge, observation, or theory, and is meant to be proven or disproven through experimentation or further investigation. Unlike a theory, which has undergone extensive testing and is widely accepted, a hypothesis is still in its infancy, awaiting validation or rejection. Think of it as a blueprint for an experiment—guiding researchers on what they expect to find and how they will test their ideas.

The Role of Hypotheses in Scientific Research 🔗

In scientific research, hypotheses serve several critical functions:

Guiding research direction: A well-constructed hypothesis provides clear direction for the research, helping scientists focus their efforts on specific aspects of a phenomenon.
Establishing a framework for testing: A hypothesis lays out the conditions under which the researcher can test the prediction, making it possible to design experiments and determine the methods of data collection.
Contributing to the scientific method: The hypothesis is one of the first steps in the scientific method, which involves observing, forming a hypothesis, testing it, and analyzing results to draw conclusions.

Characteristics of a Good Hypothesis 🔗

For a hypothesis to be useful, it must possess certain characteristics. These include:

Testability: A hypothesis must be testable through experimentation or observation. If it cannot be tested, it is not a valid hypothesis.
Falsifiability: A hypothesis should be structured in such a way that it can be proven false. If a hypothesis is never in danger of being proven wrong, it doesn’t contribute to scientific knowledge.
Clarity: A good hypothesis should be clear and specific, stating precisely what the researcher expects to find.
Predictive power: It should offer a prediction about the relationship between variables that can be tested and measured.
Relevance: The hypothesis must be relevant to the research question and grounded in existing knowledge or theory.

How Hypotheses Drive Scientific Progress 🔗

The hypothesis is not just a statement; it is the catalyst for further inquiry. Without hypotheses, scientific inquiry would lack focus and structure. By making predictions, hypotheses encourage researchers to design controlled experiments, collect data, and analyze results. This process of experimentation and testing gradually builds the body of scientific knowledge. Hypotheses drive science forward by opening new avenues of exploration, revealing patterns in data, and posing new questions for future research.

Testing the Hypothesis: Experimentation and Observation 🔗

Once a hypothesis is formulated, the next step is to test it through experiments or observations. This phase is crucial, as it determines whether the hypothesis holds true or needs to be revised. Hypotheses are typically tested through controlled experiments, where variables are manipulated to observe their effects on the dependent variable. A good experiment isolates the variables in question, ensuring that only the factor being tested influences the outcome.

Consider this example: If a researcher hypothesizes that a certain fertilizer promotes plant growth, they would design an experiment where one group of plants receives the fertilizer, and another group does not. By comparing the growth of the two groups, the researcher can test the hypothesis. If the plants with fertilizer grow significantly better, the hypothesis is supported; if not, it may need to be rethought.

Null and Alternative Hypotheses 🔗

In scientific research, hypotheses are often framed as either null or alternative hypotheses:

Null hypothesis (H₀): This is a statement that there is no effect or no relationship between variables. The null hypothesis is usually the default position, and researchers aim to test whether it can be rejected based on evidence.
Alternative hypothesis (H₁): This is the hypothesis that suggests there is a significant effect or relationship between variables. If the null hypothesis is rejected, the alternative hypothesis is considered supported.

For example, if a scientist is testing the effect of a drug on blood pressure, the null hypothesis might state that the drug has no effect on blood pressure, while the alternative hypothesis suggests that the drug lowers blood pressure. Researchers then test the null hypothesis to determine whether there is enough evidence to reject it in favor of the alternative hypothesis.

Types of Hypotheses 🔗

Hypotheses come in various forms, each suited to different research objectives. Let’s explore the most common types:

Descriptive Hypothesis 🔗

A descriptive hypothesis focuses on identifying patterns, trends, or characteristics within a particular group or phenomenon. It doesn’t predict cause-and-effect relationships but helps in gathering initial information. For example, a researcher might hypothesize that “adults who exercise regularly have lower stress levels than those who do not.” This hypothesis suggests a relationship but doesn’t establish why the relationship exists.

Relational Hypothesis 🔗

Relational hypotheses seek to determine the relationship between two or more variables, often predicting how one variable affects another. For example, a relational hypothesis could be “there is a positive correlation between hours of study and academic performance.” This type of hypothesis is often tested in experiments or through statistical analysis.

Causal Hypothesis 🔗

Causal hypotheses predict a cause-and-effect relationship between variables. For instance, “increasing the temperature of a gas will cause it to expand” is a causal hypothesis. These hypotheses are the most complex to test, as they require careful experimentation to isolate the cause and measure the effect.

Formulating a Hypothesis: A Step-by-Step Guide 🔗

Formulating a hypothesis is a crucial skill in scientific research. Here’s a step-by-step approach to guide you:

Step 1: Identify the research problem: Begin by clearly defining the problem you want to investigate. What phenomenon are you trying to explain or predict?
Step 2: Conduct background research: Review existing literature to understand what is already known about the topic. This will help you formulate a hypothesis grounded in previous findings.
Step 3: Make observations: Pay attention to patterns, relationships, or inconsistencies that might suggest an explanation.
Step 4: State the hypothesis: Formulate a clear, concise, and testable hypothesis based on your research question and observations.
Step 5: Test the hypothesis: Design experiments or observations to test your hypothesis, ensuring the methods are rigorous and the results are measurable.

Why Hypotheses Are Essential to Scientific Discovery 🔗

At its core, the hypothesis is a tool that propels scientific discovery. It transforms curiosity into a structured exploration, allowing researchers to build upon existing knowledge. Whether confirming previous theories or debunking misconceptions, the hypothesis is at the heart of scientific progress. By making predictions and then testing them through careful observation and experimentation, researchers generate new insights that can lead to groundbreaking discoveries.

Real-World Example: The Hypothesis that Changed the World 🔗

One of the most famous examples of a hypothesis leading to transformative scientific discovery comes from Albert Einstein. In 1915, he proposed his theory of general relativity, predicting that light from stars would bend as it passed near a massive object like the sun. This hypothesis was put to the test in 1919, during a solar eclipse. When astronomers observed the bending of light, it confirmed Einstein’s hypothesis and revolutionized our understanding of gravity and space-time.

Conclusion 🔗

In scientific research, hypotheses are more than just theoretical ideas; they are the bedrock of progress. They offer a structured way of approaching questions, guiding researchers to design experiments and collect data. While a hypothesis may not always be proven true, its role in driving inquiry and discovery is undeniable. Whether you’re crafting your own hypothesis or evaluating one, it’s essential to understand its purpose and potential in the broader context of scientific research.

What do you think? How do you believe hypotheses could help in solving real-world problems, like climate change or medical advancements?

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Research Methodology

1 Introduction to Research in General

Research in General
Research Circle
Tools of Research
Methods: Quantitative or Qualitative
The Product: Research Report or Papers

2 Original Unity of Philosophy and Science

Myth Philosophy and Science: Original Unity
The Myth: A Spiritual Metaphor
Myth Philosophy and Science
The Greek Quest for Unity
The Ionian School
Towards a Grand Unification Theory or Theory of Everything
Einstein’s Perennial Quest for Unity

3 Evolution of the Distinct Methods of Science

Definition of Scientific Method
The Evolution of Scientific Methods
Theory-Dependence of Observation
Scope of Science and Scientific Methods
Prevalent Mistakes in Applying the Scientific Method

4 Relation of Scientific and Philosophical Methods

Definitions of Scientific and Philosophical method
Philosophical method
Scientific method
The relation
The Importance of Philosophical and scientific methods

5 Dialectical Method

Introduction and a Brief Survey of the Method
Types of Dialectics
Dialectics in Classical Philosophy
Dialectics in Modern Philosophy
Critique of Dialectical Method

6 Rational Method

Understanding Rationalism
Rational Method of Investigation
Descartes’ Rational Method
Leibniz’ Aim of Philosophy
Spinoza’ Aim of Philosophy

7 Empirical Method

Common Features of Philosophical Method
Empirical Method
Exposition of Empiricism
Locke’s Empirical Method
Berkeley’s Empirical Method
David Hume’s Empirical Method

8 Critical Method

Basic Features of Critical Theory
On Instrumental Reason
Conception of Society
Human History as Dialectic of Enlightenment
Substantive Reason
Habermasian Critical Theory
Habermas’ Theory of Society
Habermas’ Critique of Scientism
Theory of Communicative Action
Discourse Ethics of Habermas

9 Phenomenological Method (Western and Indian)

Phenomenology in Philosophy
Phenomenology as a Method
Phenomenological Analysis of Knowledge
Phenomenological Reduction
Husserl’s Triad: Ego Cogito Cogitata
Intentionality
Understanding ‘Consciousness’
Phenomenological Method in Indian Tradition
Phenomenological Method in Religion

10 Analytical Method (Western and Indian)

Analysis in History of Philosophy
Conceptual Analysis
Analysis as a Method
Analysis in Logical Atomism and Logical Positivism
Analytic Method in Ethics
Language Analysis
Quine’s Analytical Method
Analysis in Indian Traditions

11 Hermeneutical Method (Western and Indian)

The Power (Sakti) to Convey Meaning
Three Meanings
Pre-understanding
The Semantic Autonomy of the Text
Towards a Fusion of Horizons
The Hermeneutical Circle
The True Scandal of the Text
Literary Forms

12 Deconstructive Method

The Seminal Idea of Deconstruction in Heidegger
Deconstruction in Derrida
Structuralism and Post-structuralism
Sign Signifier and Signified
Writing and Trace
Deconstruction as a Strategic Reading
The Logic of Supplement
No Outside-text

13 Method of Bibliography

Preparing to Write
Writing a Paper
The Main Divisions of a Paper
Writing Bibliography in Turabian and APA
Sample Bibliography

14 Method of Footnotes

Citations and Notes
General Hints for Footnotes
Writing Footnotes
Examples of Footnote or Endnote
Example of a Research Article

15 Method of Notes Taking

Methods of Note-taking
Note Book Style
Note taking in a Computer
Types of Note-taking
Notes from Field Research
Errors to be Avoided

16 Method of Thesis Proposal and Presentation

Preliminary Section
Presenting the Problem of the Thesis
Design of the Study
Main Body of the Thesis
Conclusion Summary and Recommendations
Reference Material

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How to Write a Strong Hypothesis | Steps & Examples - Scribbr
May 6, 2022 · 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. Example: Formulating your hypothesis Attending more lectures leads to better exam results. Tip AI tools like ChatGPT can be effectively used to brainstorm potential hypotheses.
Scientific hypothesis | Definition, Formulation, & Example ...
Nov 5, 2024 · The formulation and testing of a hypothesis is part of the scientific method, the approach scientists use when attempting to understand and test ideas about natural phenomena. The generation of a hypothesis frequently is described as a creative process and is based on existing scientific knowledge, intuition, or experience.
How to Write a Research Hypothesis- Step-By-Step Guide With ...
Mar 1, 2024 · Writing a research hypothesis is a pivotal step in any scientific inquiry, serving as the foundation upon which entire studies are built. Whether you're delving into the mysteries of particle physics or exploring the intricacies of human behaviour, formulating a clear and concise hypothesis is essential for guiding your research and drawing meaningful conclusions.
How to Write a Hypothesis: Step-By-Step Guide and Examples
Nov 5, 2024 · How can you formulate a hypothesis? To formulate a hypothesis, first state the question your experiment aims to answer and identify the independent and dependent variables. Then create an “If, Then” statement that succinctly defines the relationship between these variables. What is a hypothesis in scientific research?
How to Write a Hypothesis in 6 Steps, With Examples - Grammarly
Jun 22, 2023 · 4 Alternative hypothesis. An alternative hypothesis, abbreviated as H 1 or H A, is used in conjunction with a null hypothesis. It states the opposite of the null hypothesis, so that one and only one must be true. Examples: Plants grow better with bottled water than tap water. Professional psychics win the lottery more than other people. 5 ...
Scientific Hypotheses: Writing, Promoting, and Predicting ...
What they need at the start of their research is to formulate a scientific hypothesis that revisits conventional theories, real-world processes, and related evidence to propose new studies and test ideas in an ethical way.3 Such a hypothesis can be of most benefit if published in an ethical journal with wide visibility and exposure to relevant ...
What is a Hypothesis – Types, Examples and Writing Guide
Mar 26, 2024 · Directional Hypothesis: “An increase in employee engagement activities will lead to improved job satisfaction.” Non-Directional Hypothesis: “There is a relationship between employee engagement activities and job satisfaction.” Environmental Science. Null Hypothesis: “The introduction of green spaces does not affect urban air quality.”
Hypothesis Formulation - AIU
hypothesis is a statement that specific relationship you expect to find from your examination of these variables. When formulating the hypothesis(es) for your study, there are a few things you need to keep in mind. Good hypotheses meet the following criteria: 1) Identify the independent and dependent variables to be studied.
The Hypothesis in Science Writingaccordingly. - Penn State Berks
To begin formulating a hypothesis: A 1. Review all the information gathered during research 2. Figure out what the main question of the study is 3. Form a general statement outlining this question and the overall expectation of the experiment The goal is to create a rough version of the statement seen in Example 1 based on the
Understanding Hypotheses in Scientific Research
Sep 15, 2023 · Based on existing knowledge: While innovative, a hypothesis should be grounded in the current understanding of the subject. Formulating a hypothesis: A step-by-step process 🔗. Creating a hypothesis is a critical step in the scientific method. It’s like setting the coordinates for an exploratory voyage into the unknown waters of science.

How to Write a Research Hypothesis- Step-By-Step Guide With Examples

What is a Research Hypothesis?

How to Write a Research Hypothesis- FAQs

How do I formulate a research hypothesis?

What makes a good research hypothesis?

Should I state the direction of the relationship in my hypothesis?

Why is it important to write a research hypothesis?

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How to Write a Hypothesis: Step-By-Step Guide

Key Takeaways

Understanding a Hypothesis

Characteristics of a Good Hypothesis

Types of Hypotheses

Simple Hypothesis

Complex Hypothesis

Null Hypothesis

Alternative Hypothesis

Steps to Write a Hypothesis

Ask a Research Question

Conduct Preliminary Research

Define Your Variables

Phrase as an If-Then Statement

Collect Data to Support Your Hypothesis

Refining Your Hypothesis

Testing Your Hypothesis

Tips for Writing a Research Hypothesis

Examples of Good and Bad Hypotheses

Importance of a Testable Hypothesis

Frequently Asked Questions

What is a hypothesis in scientific research?

What are the different types of hypotheses?

How do I write a hypothesis?

Why is a testable hypothesis important?

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How to Write a Hypothesis in 6 Steps, With Examples

What is a hypothesis?

7 examples of hypotheses

1 Simple hypothesis

2 Complex hypothesis

3 Null hypothesis

4 Alternative hypothesis

5 Logical hypothesis

6 Empirical hypothesis

7 Statistical hypothesis

What makes a good hypothesis?

Cause and effect

Testable prediction

Independent and dependent variables

Candid language

Adherence to ethics

How to write a hypothesis in 6 steps

2 Conduct preliminary research

3 Define your variables

4 Phrase it as an if-then statement

5 Collect data to support your hypothesis

6 Write with confidence

Scientific Hypotheses: Writing, Promoting, and Predicting Implications

INTRODUCTION

EXAMPLES OF INFLUENTIAL SCIENTIFIC HYPOTHESES

WRITING SCIENTIFIC HYPOTHESES

Table 1. Characteristics of scientific hypotheses and narrative and systematic reviews.

ETHICAL IMPLICATIONS

WHERE TO PUBLISH HYPOTHESES

CITATIONS AND SOCIAL MEDIA ATTENTION

Fig. 1. Number of Scopus-indexed items citing Strachan's hygiene hypothesis in 1992–2019 (as of August 28, 2019).

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What is a Hypothesis – Types, Examples and Writing Guide

Types of Hypotheses

1. Null Hypothesis (H₀)

2. Alternative Hypothesis (H₁ or Hₐ)