what the difference between hypothesis and thesis

The Real Differences Between Thesis and Hypothesis (With table)

A thesis and a hypothesis are two very different things, but they are often confused with one another. In this blog post, we will explain the differences between these two terms, and help you understand when to use which one in a research project.

As a whole, the main difference between a thesis and a hypothesis is that a thesis is an assertion that can be proven or disproven, while a hypothesis is a statement that can be tested by scientific research. 

We probably need to expand a bit on this topic to make things clearer for you, let’s start with definitions and examples.

Definitions

As always, let’s start with the definition of each term before going further.

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If you are writing a paper about the effects of climate change on the environment, your thesis might be “Climate change is causing irreparable damage to our planet, and we must take action to prevent further damage”.

If your hypothesis is correct, then further research should be able to confirm it. However, if your hypothesis is incorrect, research will disprove it. Either way, a hypothesis is an important part of the scientific process.

The word “hypothesis” comes from the Greek words “hupo,” meaning “under”, and “thesis” that we just explained.

Argumentation vs idea

A hypothesis is only a statement that need to be tested by observation or experimentation.

5 mains differences between thesis and hypothesis

Thesis and hypothesis are different in several ways, here are the 5 keys differences between those terms:

Is there a difference between a thesis and a claim?

Is a hypothesis a prediction.

No, a hypothesis is not a prediction. A prediction is a statement about what you think will happen in the future, whereas a hypothesis is a statement about what you think is causing a particular phenomenon.

What’s the difference between thesis and dissertation?

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Answered By: APUS Librarians Last Updated: Apr 15, 2022     Views: 128659

Both the hypothesis statement and the thesis statement answer a research question. 

• A hypothesis is a statement that can be proved or disproved. It is typically used in quantitative research and predicts the relationship between variables.  
• A thesis statement is a short, direct sentence that summarizes the main point or claim of an essay or research paper. It is seen in quantitative, qualitative, and mixed methods research. A thesis statement is developed, supported, and explained in the body of the essay or research report by means of examples and evidence.

Every research study should contain a concise and well-written thesis statement. If the intent of the study is to prove/disprove something, that research report will also contain a hypothesis statement.

NOTE: In some disciplines, the hypothesis is referred to as a thesis statement! This is not accurate but within those disciplines it is understood that "a short, direct sentence that summarizes the main point" will be included.

For more information, see The Research Question and Hypothesis (PDF file from the English Language Support, Department of Student Services, Ryerson University).

How do I write a good thesis statement?

How do I write a good hypothesis statement?

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Home » Education » Difference Between Thesis and Hypothesis

Difference Between Thesis and Hypothesis

Main difference –  thesis vs hypothesis                           .

Thesis and hypothesis are two common terms that are often found in research studies. Hypothesis is a logical proposition that is based on existing knowledge that serves as the starting point of an investigation. A thesis is a statement that is put forward as a premise to be maintained or proved. The main difference between thesis and hypothesis is that thesis is found in all research studies whereas a hypothesis is mainly found in experimental quantitative research studies.

This article explains,

1. What is a Thesis?      – Definition, Features, Function

2. What is a Hypothesis?      – Definition, Features, Function

What is a Thesis

The word thesis has two meanings in a research study. Thesis can either refer to a dissertation or a thesis statement. Thesis or dissertation is the long essay or document that consists of the research study.  Thesis can also refer to a theory or statement that is used as a premise to be maintained or proved.

The thesis statement in a research article is a sentence found at the beginning of the paper that presents the main argument of the paper. The rest of the document will gather, organize and present evidence to support this argument. The thesis statement will basically present the topic of the paper and indicate what position the researcher is going to take in relation to this topic. A thesis statement can generally be found at the end of the first paragraph (introductory paragraph) of the paper.

What is a Hypothesis

A hypothesis is a logical assumption based on available evidence. Hypothesis is defined as “a supposition or proposed explanation made on the basis of limited evidence as a starting point for further investigation” in the Oxford dictionary and as “an idea or theory that is not proven but that leads to further study or discussion” in the Merriam-Webster dictionary. In simple words, it is an educated guess that is not proven with concrete scientific evidence. Once it is scientifically tested and proven, it becomes a theory. However, it is important to note that a hypothesis can be accurate or inaccurate.

Hypotheses are mostly used in experiments and research studies. However, hypotheses are not used in every research study. They are mostly used in quantitative research studies  that deal with experiments. Hypotheses are often used to test a specific model or theory . They can be used only when the researcher has sufficient knowledge about the subject since hypothesis are always based on the existing knowledge. Once the hypothesis is built, the researcher can find and analyze data and use them to prove or disprove the hypothesis.

Thesis: A thesis is a “statement or theory that is put forward as a premise to be maintained or proved” or a “long essay or dissertation involving personal research, written by a candidate for a university degree” (Oxford dictionary).

Hypothesis: A hypothesis is “a supposition or proposed explanation made on the basis of limited evidence as a starting point for further investigation” (Oxford dictionary).

Thesis: Thesis statement can be found in all research papers.

Hypothesis: Hypotheses are usually found in experimental quantitative research studies.

Thesis: Thesis statement may explain the hypothesis and how the researcher intends to support it.

Hypothesis: Hypothesis is an educated guess based on the existing knowledge.

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Thesis Vs Hypothesis: Understanding The Basis And The Key Differences

Hypothesis vs. thesis: They sound similar and seem to discuss the same thing. However, these terms have vastly different meanings and purposes. You may have encountered these concepts in school or research, but understanding them is key to executing quality work. 

In this article, I’ll discuss hypothesis vs. thesis, break down their differences, and show you how to apply this knowledge to create quality written works. Let’s get to it!

Thesis vs. Hypothesis: Understanding the Basis

The power of a thesis.

A thesis statement is typically found at the end of the introduction in an essay or research paper, succinctly summarizing the overarching theme.

Crafting a strong thesis

Hypothesis: the scientific proposition.

In contrast, a hypothesis is a tentative proposition or educated guess. It is the initial step in the scientific method, where researchers formulate a hunch to test their assumptions and theories. 

Formulating a hypothesis

Key differences between thesis vs. hypothesis, 1. nature of statement, 3. testability, 4. research stage, 6. examples.

These differences highlight the distinct roles that the thesis and hypothesis play in academic writing and scientific research, with one providing a point of argumentation and the other guiding the scientific inquiry process.

Can a hypothesis become a thesis?

Do all research papers require a thesis, can a thesis be proven wrong.

Yes. The purpose of a thesis is not only to prove but also to encourage critical analysis. It can be proven wrong with compelling counterarguments and evidence.

How long should a thesis statement be?

Is a hypothesis only used in scientific research, can a hypothesis be vague.

No. When creating a hypothesis, it’s important to make it clear and able to be tested. Developing experiments and making conclusions based on the results can be difficult if the hypothesis needs clarification.

Final Thoughts

In conclusion, understanding the differences between a hypothesis and a thesis is vital to crafting successful research projects and academic papers. While they may seem interchangeable at first glance, these two concepts serve distinct purposes in the research process. 

So, the next time you embark on a research project, take the time to ensure that you understand the fundamental difference between a hypothesis and a thesis. Doing so can lead to more focused, meaningful research that advances knowledge and understanding in your field.

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B oth the hypothesis statement and the thesis statement answer the research question of the study.  When the statement is one that can be proved or disproved, it is an hypothesis statement.  If, instead, the statement specifically shows the intentions/objectives/position of the researcher, it is a thesis statement.

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

A thesis statement is a short, direct sentence that summarizes the main point or claim of an essay or research paper. It is seen in quantitative, qualitative, and mixed methods research.  A thesis statement is developed, supported, and explained in the body of the essay or research report by means of examples and evidence.

Every research study should contain a concise and well-written thesis statement. If the intent of the study is to prove/disprove something, that research report will also contain an hypothesis statement.

Jablonski , Judith. What is the difference between a thesis statement and an hypothesis statement? Online Library. American Public University System. Jun 16, 2014. Web.   http://apus.libanswers.com/faq/2374

Let’s say you are interested in the conflict in Darfur, and you conclude that the issues you wish to address include the nature, causes, and effects of the conflict, and the international response. While you could address the issue of international response first, it makes the most sense to start with a description of the conflict, followed by an exploration of the causes, effects, and then to discuss the international response and what more could/should be done.

This hypothetical example may lead to the following title, introduction, and statement of questions:

Conflict in Darfur: Causes, Consequences, and International Response       This paper examines the conflict in Darfur, Sudan. It is organized around the following questions: (1) What is the nature of the conflict in Darfur? (2) What are the causes and effects of the conflict? (3) What has the international community done to address it, and what more could/should it do?

Following the section that presents your questions and background, you will offer a set of responses/answers/(hypo)theses. They should follow the order of the questions. This might look something like this, “The paper argues/contends/ maintains/seeks to develop the position that...etc.” The most important thing you can do in this section is to present as clearly as possible your best thinking on the subject matter guided by course material and research. As you proceed through the research process, your thinking about the issues/questions will become more nuanced, complex, and refined. The statement of your theses will reflect this as you move forward in the research process.

So, looking to our hypothetical example on Darfur:

The current conflict in Darfur goes back more than a decade and consists of fighting between government-supported troops and residents of Darfur. The causes of the conflict include x, y, and z. The effects of the conflict have been a, b, and c. The international community has done 0, and it should do 1, 2, and 3.

Once you have setup your thesis you will be ready to begin amassing supporting evidence for you claims. This is a very important part of the research paper, as you will provide the substance to defend your thesis.

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Thesis vs. Hypothesis — What's the Difference?

Difference Between Thesis and Hypothesis

Table of contents, key differences, comparison chart, position in study, compare with definitions, common curiosities, what happens if a hypothesis is refuted, is a thesis always present in an essay, is a phd dissertation a thesis, what follows after stating a thesis in an essay, can a hypothesis turn into a theory, can a hypothesis be proven true permanently, is the thesis statement the same as a thesis, can a single research paper have multiple theses, is a hypothesis an opinion, are hypotheses only used in scientific fields, who presents a thesis, how specific should a hypothesis be, does a thesis require evidence, why are hypotheses essential in science, share your discovery.

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

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

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

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

Research Hypothesis 101

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

What is a hypothesis?

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

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

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

Hypothesis: sleep impacts academic performance.

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

But that’s not good enough…

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

What is a research hypothesis?

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

Let’s take a look at these more closely.

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Hypothesis Essential #1: Specificity & Clarity

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

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

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

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

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

Hypothesis Essential #2: Testability (Provability)

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

For example, consider the hypothesis we mentioned earlier:

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

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

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

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

Defining A Research Hypothesis

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

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

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

What about the null hypothesis?

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

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

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

And there you have it – hypotheses in a nutshell. 

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

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

17 Comments

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

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

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

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

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

It’s a counter-proposal to be proven as a rejection

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

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

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

could you please elaborate it more

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

This is very helpful

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

Excellent. Thanks for being clear and sound about the research methodology and hypothesis (quantitative research)

I have only a simple question regarding the null hypothesis. – Is the null hypothesis (Ho) known as the reversible hypothesis of the alternative hypothesis (H1? – How to test it in academic research?

this is very important note help me much more

Hi” best wishes to you and your very nice blog” 

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• How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples

Published on May 6, 2022 by Shona McCombes . Revised on November 20, 2023.

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

Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

Table of contents

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

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

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

Variables in hypotheses

Hypotheses propose a relationship between two or more types of variables .

• An independent variable is something the researcher changes or controls.
• A dependent variable is something the researcher observes and measures.

If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias  will affect your results.

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

Prevent plagiarism. Run a free check.

Step 1. ask a question.

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

Step 2. Do some preliminary research

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

At this stage, you might construct a conceptual framework to ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize more complex constructs.

Step 3. Formulate your hypothesis

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

4. Refine your hypothesis

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

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

5. Phrase your hypothesis in three ways

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

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

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

6. Write a null hypothesis

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

• H 0 : The number of lectures attended by first-year students has no effect on their final exam scores.
• H 1 : The number of lectures attended by first-year students has a positive effect on their final exam scores.

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

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

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

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

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

Cite this Scribbr article

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McCombes, S. (2023, November 20). How to Write a Strong Hypothesis | Steps & Examples. Scribbr. Retrieved August 2, 2024, from https://www.scribbr.com/methodology/hypothesis/

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The Craft of Writing a Strong Hypothesis

Table of Contents

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

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

What is a Hypothesis?

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

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

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

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

Different Types of Hypotheses‌

Types of hypotheses

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

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

1. Null hypothesis

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

2. Alternative hypothesis

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

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

3. Simple hypothesis

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

4. Complex hypothesis

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

5. Associative and casual hypothesis

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

6. Empirical hypothesis

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

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

7. Statistical hypothesis

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

Characteristics of a Good Hypothesis

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

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

Separating a Hypothesis from a Prediction

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

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

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

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

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

Finally, How to Write a Hypothesis

Quick tips on writing a hypothesis

1.  Be clear about your research question

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

2. Carry out a recce

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

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

3. Create a 3-dimensional hypothesis

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

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

4. Write the first draft

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

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

5. Proof your hypothesis

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

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

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

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

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

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

Frequently Asked Questions (FAQs)

1. what is the definition of hypothesis.

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

2. What is an example of hypothesis?

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

3. What is an example of null hypothesis?

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

4. What are the types of research?

• Fundamental research

• Applied research

• Qualitative research

• Quantitative research

• Mixed research

• Exploratory research

• Longitudinal research

• Cross-sectional research

• Field research

• Laboratory research

• Fixed research

• Flexible research

• Action research

• Policy research

• Classification research

• Comparative research

• Causal research

• Inductive research

• Deductive research

5. How to write a hypothesis?

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

• Avoid wordiness by keeping it simple and brief.

• Your hypothesis should contain observable and testable outcomes.

• Your hypothesis should be relevant to the research question.

6. What are the 2 types of hypothesis?

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

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

7. Difference between research question and research hypothesis?

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

8. What is plural for hypothesis?

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

9. What is the red queen hypothesis?

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

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

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

11. When to reject null hypothesis?

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

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Key Differences

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What is the Correct Way to Write a Hypothesis? Expert Tips and Examples

Crafting a solid hypothesis is a crucial step in the scientific research process. A well-formulated hypothesis not only guides your research but also provides a clear focus for your study. This article delves into expert tips and examples to help you write a strong hypothesis, ensuring your research is grounded in a solid theoretical framework.

Key Takeaways

• A hypothesis should be clear and precise, providing a specific prediction that can be tested.
• Preliminary research is essential to formulate a well-informed hypothesis based on existing literature and data.
• A strong hypothesis must be testable and falsifiable, meaning it can be proven or disproven through experimentation or observation.
• It is important to differentiate between null and alternative hypotheses, as both play crucial roles in scientific research.
• Avoid common pitfalls such as overly broad statements and ambiguous language to ensure your hypothesis is effective and meaningful.

Understanding the Fundamentals of a Hypothesis

A hypothesis is a foundational element in scientific research, serving as a preliminary answer to a research question. Understanding its fundamentals is crucial for any researcher. A well-crafted hypothesis not only guides the direction of your study but also provides a basis for statistical storytelling: understanding and applying key stats in experimental research .

Steps to Formulating a Strong Hypothesis

Identifying the research question.

The first step in formulating a strong hypothesis is to identify the main research question . This involves recognizing a pattern or phenomenon that piques your interest and then asking a specific question that your hypothesis will aim to answer. This step is crucial as it sets the direction for your targeted research .

Conducting Preliminary Research

Before you can formulate a hypothesis, you need to conduct preliminary research. This involves gathering as much information as possible about your topic. By reviewing existing literature and studies, you can gain insights into what is already known and identify gaps that your research could fill. This step ensures that your hypothesis is grounded in existing knowledge and is relevant to the field.

Formulating the Hypothesis Statement

Once you have identified your research question and conducted preliminary research, the next step is to formulate your hypothesis statement. A well-crafted hypothesis should be clear, specific, and testable. It should propose a relationship between variables that can be examined through experimentation or observation. Remember, a strong hypothesis not only predicts an outcome but also provides a basis for further investigation.

Characteristics of a Well-Written Hypothesis

A well-written hypothesis is essential for guiding your research and ensuring that your study is both meaningful and scientifically valid. Clarity and precision are paramount; your hypothesis should be articulated in a way that leaves no room for ambiguity. This means using specific language and clearly defining any terms or variables involved. A hypothesis must also be testable and falsifiable, meaning it should be structured in a way that allows for empirical testing and the possibility of being proven wrong. This is crucial for maintaining the scientific integrity of your research. Lastly, your hypothesis should be directly relevant to your research question, providing a focused direction for your study. By adhering to these characteristics, you can formulate a hypothesis that is both robust and reliable.

Types of Hypotheses in Research

Understanding the various types of hypotheses is crucial for any researcher. Each type serves a unique purpose and is used in different contexts to address the research question effectively.

Examples of Effective Hypotheses

Hypotheses in natural sciences.

In the natural sciences, hypotheses often predict relationships between variables based on empirical evidence. For instance, a hypothesis might state, "Plants exposed to higher levels of sunlight will grow faster than those in shaded areas." This hypothesis is clear and testable , making it a strong candidate for scientific investigation.

Hypotheses in Social Sciences

Social science hypotheses frequently address human behavior and societal trends. An example could be, "Individuals who engage in regular physical activity report higher levels of happiness compared to those who do not." This hypothesis is relevant to the research question and can be tested through surveys and observational studies.

Hypotheses in Applied Research

Applied research often focuses on practical problems and solutions. A typical hypothesis might be, "Implementing a four-day workweek will increase employee productivity." This hypothesis is specific and actionable , providing a clear direction for research and potential policy changes.

Common Pitfalls and How to Avoid Them

When crafting a hypothesis, it's crucial to be aware of common pitfalls that can undermine your research. Avoiding these mistakes will enhance the quality and reliability of your study.

Expert Tips for Writing a Hypothesis

Consulting existing literature.

Before you start formulating your hypothesis, it's crucial to delve into existing literature. This step helps in demystifying the concept of a thesis statement and provides a foundation for your research. By reviewing previous studies, you can identify gaps in the research and build upon them. This not only strengthens your hypothesis but also ensures its relevance in the academic community.

Peer Review and Feedback

Engaging with peers and mentors for feedback is an invaluable part of the hypothesis-writing process. Constructive criticism can help you refine your hypothesis, making it more precise and testable. Don't hesitate to share your drafts and be open to suggestions. This collaborative approach can significantly reduce thesis anxiety and improve the quality of your work.

Iterative Refinement

Writing a hypothesis is not a one-time task; it requires iterative refinement. Start with a broad idea and gradually narrow it down through multiple revisions. This process involves continuously testing and tweaking your hypothesis to ensure it aligns with your research objectives. Remember, a well-crafted hypothesis is the result of meticulous planning and constant improvement.

Crafting a solid hypothesis is crucial for the success of your thesis. Our experts at Research Rebels have compiled essential tips to guide you through this process. Don't let uncertainty hold you back. Visit our website to explore our comprehensive Thesis Action Plan and claim your special offer now !

In conclusion, writing a hypothesis is a fundamental step in the scientific research process that requires careful consideration and precision. By following the expert tips and examples provided in this article, researchers can craft hypotheses that are clear, testable, and relevant to their studies. A well-formulated hypothesis not only guides the direction of the research but also provides a framework for analyzing results and drawing meaningful conclusions. As such, mastering the art of hypothesis writing is essential for any researcher aiming to contribute valuable insights to their field of study.

Frequently Asked Questions

What is a hypothesis.

A hypothesis is a tentative statement predicting a relationship between variables, which can be tested through scientific research.

Why is a hypothesis important in scientific research?

A hypothesis provides a focused direction for research, allowing scientists to make predictions and test their validity through experimentation.

What are the key characteristics of a well-written hypothesis?

A well-written hypothesis should be clear, precise, testable, falsifiable, and relevant to the research question.

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

A null hypothesis states that there is no effect or relationship between variables, while an alternative hypothesis suggests that there is an effect or relationship.

How can I ensure my hypothesis is testable?

To ensure your hypothesis is testable, it should be specific and measurable, with clearly defined variables and a methodology for testing.

What are common mistakes to avoid when writing a hypothesis?

Common mistakes include making hypotheses that are too broad, using ambiguous language, and failing to ensure the hypothesis is testable.

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What is the difference between hypothesis, thesis statement and research goal?

Can someone explain the difference between hypothesis, thesis statement and research goal based on an example?

• terminology

• 1 You should mention which subject you are in. 'Hypothesis' has opposite meanings in maths and physics. –  Jessica B Commented May 31, 2018 at 11:22

2 Answers 2

I had this same question recently and did some research on it. The definitions I found weren't consistent, but from them I derived the following.

Thesis statement -- A definitive statement about the way the world (or your system of interest) works, especially what is most important in causing or influencing the behavior of the system.

"Family expectations has primary significance on the performance in college for Latino girls in the Western US" is an example of a thesis statement.

Research goal -- Expresses what you hope to learn or shed light on in your research. Specifically, the goal should specify what type of results you are hoping to achieve. It contextualizes your work in relation to other research, especially theory. It also feeds into your choice of method.

"My research goal is to develop a theoretical model of cultural influence on college performance, contextualized by gender and ethnicity" is an example of a research goal.

Hypotheses -- What specific conditions or relations do you aim to test or evaluate in your research. Any research that does not include a method for hypothesis testing should not claim to test hypotheses. A hypothesis statement must be specific enough that it is testable by the methods you choose, and also it should be falsifiable -- i.e. it is clear what evidence might prove the hypothesis false, and such evidence should be plausible and possible.

"Low family expectations has a detrimental effect on the college completion rate and time-to-complete for high-achieving Latino girls" is an example of a hypothesis statement.

Notice how there are specific, testable conditions and metrics -- "college completion rates" and "time-to-complete". These conditions should appear as metrics in your research methods -- i.e. instruments and analysis methods.

A thesis statement usually helps guide the research paper. It is a short sentence or summary containing the central idea of the research paper. It helps a reader have a clear glimpse of what the paper is about.

The Hypothesis statement comes in different format but with the intent to help prove or disprove a phenomenon. The hypothesis can help defend, support, explain or disprove, argue against the thesis statement.Usually the hypothesis measures specific issues or variables-two or more and therefore should be testable. The thesis statement creates a background while the hypothesis creates a means to measure the interrelationship.

The research goal takes a look into the future of your study or research paper. |It tries to help you state what the outcomes you seek to achieve by the research work. With a research goal you can set specific milestones to accomplish at the end of the research work.

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Thesis vs Hypothesis - What's the difference?

Hypothesis is a related term of thesis ., hypothesis is a synonym of thesis ., as nouns the difference between thesis and hypothesis, derived terms, related terms, external links.

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Thesis vs Hypothesis vs Theory: the Differences and examples

thesis hypothesis and theory

Many students may have a hard time understanding the differences between a thesis, a hypothesis, and a theory. It is important to understand their differences. Such an understanding will be instrumental.

More so, when writing complex research papers that require a thesis that has a hypothesis and utilizes theories. We have gathered from responses of our college writing service that the difference between the three is confusing.

That being said, this article is meant to explain the differences between a thesis, a hypothesis, and a theory. 

Difference between Hypothesis and Thesis

There are major differences between hypothesis and thesis. While they seem to be related on the face, their differences are huge both in concept and practice.

A hypothesis is a proposed explanation of something or a phenomenon. A scientific hypothesis uses a scientific method that requires any hypothesis to be tested. As such, scientists and researchers base their hypothesis on observations that have been previously made and that which cannot be explained by the available or prevailing scientific theories.

From the definition of a hypothesis, you can see that theories must be included in any scientific method. This is the reason why this article tries to differentiate a thesis, a hypothesis, and a theory. 

Moving forward, a thesis can be defined as a written piece of academic work that is submitted by students to attain a university degree. However, on a smaller scale, there is something that is referred to as a thesis statement.

This is written at the introduction of a research paper or essay that is supported by a credible argument. The link between a hypothesis and thesis is that a thesis is a distinction or an affirmation of the hypothesis.

What this means is that whenever a research paper contains a hypothesis, there should be a thesis that validates it. 

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What is a Hypothesis?

A hypothesis can be defined as the proposed or suggested explanation for an occurrence, something, or a phenomenon. It should be testable through scientific methods. The reason why scholarly works should have a hypothesis is that the observed phenomena could not be explained using the prevailing scientific theories hence the reason why it should be tested. 

Testing the hypothesis may result in the development of new or improved scientific theories that are beneficial to the discipline and society in general. 

What is a Thesis?

A thesis is a written piece of academic work that is submitted by students to attain a university degree. When a thesis is used as a stand-alone word, it denotes academic papers written by university students. It is mostly written by those pursuing postgraduate degrees, at the end of their courses. They demonstrate their proficiency in their disciplines and the topics they have selected for research. 

However, when a thesis is used to refer to a statement, it denotes the statement that is written at the introduction of a research paper or essay. A thesis is supported by a credible argument.

Every research paper must have a thesis statement that acts as a guide to what the research will be all about. It is possible to receive very poor grades or even score a zero if your research paper lacks the thesis statement. 

What is a Theory?

A theory can be defined as a rational form of abstract perspectives or thinking concerning the results of such thinking or a phenomenon. The process of rational and contemplative thinking is mostly associated with processes such as research or observational study.

As such, a theory can be considered to belong to both scientific and non-scientific disciplines. Theories can also belong to no discipline.

From a modernistic scientific approach, a theory can mean scientific theories that have been well confirmed to explain nature and that are created in such a way that they are consistent with the standard scientific method. A theory should fulfill all the criteria required by modern-day science. 

A theory should be described in a way that scientific tests that have been conducted can provide empirical support or contradiction to the theory.

Because of the nature by which scientific theories are developed, they tend to be the most rigorous, reliable, and comprehensive when it comes to describing and supporting scientific knowledge. 

The connection between a theory and a hypothesis is that when a theory has not yet been proven, it can be referred to as a hypothesis.

The thing about theories is that they are not meant to help the scientist or researcher reach a particular goal. Rather, a theory is meant to guide the process of finding facts about a phenomenon or an observation. 

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Difference between a Theory and Thesis

A theory is a rational form of abstract perspectives or thinking concerning the results of such thinking or a phenomenon. The process of rational and contemplative thinking is mostly associated with processes such as research or observational study. On the other hand, a thesis is a written piece of academic work that is submitted by students to attain a university degree.

It denotes academic papers that are written by students in the university, especially those pursuing postgraduate degrees, at the end of their courses to demonstrate their proficiency in their disciplines and the topics they have selected for research. 

To understand the application of these, read our guide on the difference between a research paper and a thesis proposal to get a wider view.

How to write a Good Hypothesis

1. asking a question.

Asking a question is the first step in the scientific method and the question should be based on  who, what, where, when, why,  and  how . The question should be focused, specific, and researchable.

2. Gathering preliminary research 

This is the process of collecting relevant data. It can be done by researching academic journals, conducting case studies, observing phenomena, and conducting experiments. 

3. Formulating an answer

When the research is completed, you should think of how best to answer the question and defend your position. The answer to your question should be objective. 

4. Writing the hypothesis

When your answer is ready, you can move to the next step of formulating the hypothesis. A good hypothesis should contain relevant variables, predicted outcomes, and a study group that can include non-human things. The hypothesis should not be a question but a complete statement. 

5. Refining the hypothesis

Though you may skip this step, it is advisable to include it because your study may involve two groups or be a correlational study. Refining the hypothesis will ensure that you have stated the difference or relationship you expect to find. 

6. Creating a null and alternative hypotheses

A null hypothesis (H0) will postulate that there is no evidence to support the difference. On the other hand, an alternative hypothesis (H1) posits that there is evidence in support of the difference. 

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Frequently Asked Questions

Difference between thesis and hypothesis example.

Thesis:  High levels of alcohol consumption have detrimental effects on your health, such as weight gain, heart disease, and liver complications.

Hypothesis:  The people who consume high levels of alcohol experience detrimental effects on their health such as weight gain, heart disease, and liver complications. 

What is the difference between a summary and a thesis statement?

A summary is a brief account or statement of the main points from the researches. A thesis statement is a statement that is written at the end of the introduction of a research paper or essay that summarizes the main claims of the paper. 

Difference between hypothesis and statement of the problem

A hypothesis can be defined as the proposed or suggested explanation for an occurrence, something, or a phenomenon. The same should be testable through scientific methods. Conversely, a statement of a problem is a concise description of the issue to be addressed on how it can be improved. 

When not handling complex essays and academic writing tasks, Josh is busy advising students on how to pass assignments. In spare time, he loves playing football or walking with his dog around the park.

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“Theory” vs. “Hypothesis”: What Is The Difference?

Chances are you’ve heard of the TV show The Big Bang Theory . Lots of people love this lighthearted sitcom for its quirky characters and their relationships, but others haven’t even given the series a chance for one reason: they don’t like science and assume the show is boring.

However, it only takes a few seconds with Sheldon and Penny to disprove this assumption and realize that this theory ab0ut The Big Bang Theory is wrong—it isn’t a scientific snoozefest.

But wait: is it a theory or a  hypothesis about the show that leads people astray? And would the actual big bang theory— the one that refers to the beginning of the universe—mean the same thing as a big bang hypothesis ?

Let’s take a closer look at theory and hypothesis to nail down what they mean.

What does theory mean?

As a noun, a theory is a group of tested general propositions “commonly regarded as correct, that can be used as principles of explanation and prediction for a class of phenomena .” This is what is known as a scientific   theory , which by definition is “an understanding that is based on already tested data or results .” Einstein’s theory of relativity and the  theory of evolution are both examples of such tested propositions .

Theory is also defined as a proposed explanation you might make about your own life and observations, and it’s one “whose status is still conjectural and subject to experimentation .” For example:  I’ve got my own theories about why he’s missing his deadlines all the time.  This example refers to an idea that has not yet been proven.

There are other uses of the word theory as well.

• In this example,  theory is “a body of principles or theorems belonging to one subject.” It can be a branch of science or art that deals with its principles or methods .
• For example: when she started to follow a new parenting theory based on a trendy book, it caused a conflict with her mother, who kept offering differing opinions .

First recorded in 1590–1600, theory originates from the Late Latin theōria , which stems from the Greek theōría. Synonyms for theory include approach , assumption , doctrine , ideology , method , philosophy , speculation , thesis , and understanding .

What does hypothesis mean?

Hypothesis is a noun that means “a proposition , or set of propositions, set forth as an explanation” that describe “some specified group of phenomena.” Sounds familiar to theory , no?

But, unlike a theory , a scientific  hypothesis is made before testing is done and isn’t based on results. Instead, it is the basis for further investigation . For example: her working hypothesis is that this new drug also has an unintended effect on the heart, and she is curious what the clinical trials  will show .

Hypothesis also refers to “a proposition assumed as a premise in an argument,” or “mere assumption or guess.” For example:

• She decided to drink more water for a week to test out her hypothesis that dehydration was causing her terrible headaches.
• After a night of her spouse’s maddening snoring, she came up with the hypothesis that sleeping on his back was exacerbating the problem.

Hypothesis was first recorded around 1590–1600 and originates from the Greek word hypóthesis (“basis, supposition”). Synonyms for hypothesis include: assumption , conclusion , conjecture , guess , inference , premise , theorem , and thesis .

How to use each

Although theory in terms of science is used to express something based on extensive research and experimentation, typically in everyday life, theory is used more casually to express an educated guess.

So in casual language,  theory and hypothesis are more likely to be used interchangeably to express an idea or speculation .

In most everyday uses, theory and hypothesis convey the same meaning. For example:

• Her opinion is just a theory , of course. She’s just guessing.
• Her opinion is just a hypothesis , of course. She’s just guessing.

It’s important to remember that a scientific   theory is different. It is based on tested results that support or substantiate it, whereas a hypothesis is formed before the research.

For example:

• His  hypothesis  for the class science project is that this brand of plant food is better than the rest for helping grass grow.
• After testing his hypothesis , he developed a new theory based on the experiment results: plant food B is actually more effective than plant food A in helping grass grow.

In these examples, theory “doesn’t mean a hunch or a guess,” according to Kenneth R. Miller, a cell biologist at Brown University. “A theory is a system of explanations that ties together a whole bunch of facts. It not only explains those facts, but predicts what you ought to find from other observations and experiments.”

So if you have a concept that is based on substantiated research, it’s a theory .

But if you’re working off of an assumption that you still need to test, it’s a hypothesis .

So remember, first comes a hypothesis , then comes theory . Now who’s ready for a  Big Bang Theory marathon?

Now that you’ve theorized and hypothesized through this whole article … keep testing your judgment (Or is it judgement?). Find out the correct spelling here!

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This is the Difference Between a Hypothesis and a Theory

What to Know A hypothesis is an assumption made before any research has been done. It is formed so that it can be tested to see if it might be true. A theory is a principle formed to explain the things already shown in data. Because of the rigors of experiment and control, it is much more likely that a theory will be true than a hypothesis.

As anyone who has worked in a laboratory or out in the field can tell you, science is about process: that of observing, making inferences about those observations, and then performing tests to see if the truth value of those inferences holds up. The scientific method is designed to be a rigorous procedure for acquiring knowledge about the world around us.

In scientific reasoning, a hypothesis is constructed before any applicable research has been done. A theory, on the other hand, is supported by evidence: it's a principle formed as an attempt to explain things that have already been substantiated by data.

Toward that end, science employs a particular vocabulary for describing how ideas are proposed, tested, and supported or disproven. And that's where we see the difference between a hypothesis and a theory .

A hypothesis is an assumption, something proposed for the sake of argument so that it can be tested to see if it might be true.

In the scientific method, the hypothesis is constructed before any applicable research has been done, apart from a basic background review. You ask a question, read up on what has been studied before, and then form a hypothesis.

What is a Hypothesis?

A hypothesis is usually tentative, an assumption or suggestion made strictly for the objective of being tested.

When a character which has been lost in a breed, reappears after a great number of generations, the most probable hypothesis is, not that the offspring suddenly takes after an ancestor some hundred generations distant, but that in each successive generation there has been a tendency to reproduce the character in question, which at last, under unknown favourable conditions, gains an ascendancy. Charles Darwin, On the Origin of Species , 1859 According to one widely reported hypothesis , cell-phone transmissions were disrupting the bees' navigational abilities. (Few experts took the cell-phone conjecture seriously; as one scientist said to me, "If that were the case, Dave Hackenberg's hives would have been dead a long time ago.") Elizabeth Kolbert, The New Yorker , 6 Aug. 2007

What is a Theory?

A theory , in contrast, is a principle that has been formed as an attempt to explain things that have already been substantiated by data. It is used in the names of a number of principles accepted in the scientific community, such as the Big Bang Theory . Because of the rigors of experimentation and control, its likelihood as truth is much higher than that of a hypothesis.

It is evident, on our theory , that coasts merely fringed by reefs cannot have subsided to any perceptible amount; and therefore they must, since the growth of their corals, either have remained stationary or have been upheaved. Now, it is remarkable how generally it can be shown, by the presence of upraised organic remains, that the fringed islands have been elevated: and so far, this is indirect evidence in favour of our theory . Charles Darwin, The Voyage of the Beagle , 1839 An example of a fundamental principle in physics, first proposed by Galileo in 1632 and extended by Einstein in 1905, is the following: All observers traveling at constant velocity relative to one another, should witness identical laws of nature. From this principle, Einstein derived his theory of special relativity. Alan Lightman, Harper's , December 2011

Non-Scientific Use

In non-scientific use, however, hypothesis and theory are often used interchangeably to mean simply an idea, speculation, or hunch (though theory is more common in this regard):

The theory of the teacher with all these immigrant kids was that if you spoke English loudly enough they would eventually understand. E. L. Doctorow, Loon Lake , 1979 Chicago is famous for asking questions for which there can be no boilerplate answers. Example: given the probability that the federal tax code, nondairy creamer, Dennis Rodman and the art of mime all came from outer space, name something else that has extraterrestrial origins and defend your hypothesis . John McCormick, Newsweek , 5 Apr. 1999 In his mind's eye, Miller saw his case suddenly taking form: Richard Bailey had Helen Brach killed because she was threatening to sue him over the horses she had purchased. It was, he realized, only a theory , but it was one he felt certain he could, in time, prove. Full of urgency, a man with a mission now that he had a hypothesis to guide him, he issued new orders to his troops: Find out everything you can about Richard Bailey and his crowd. Howard Blum, Vanity Fair , January 1995

And sometimes one term is used as a genus, or a means for defining the other:

Laplace's popular version of his astronomy, the Système du monde , was famous for introducing what came to be known as the nebular hypothesis , the theory that the solar system was formed by the condensation, through gradual cooling, of the gaseous atmosphere (the nebulae) surrounding the sun. Louis Menand, The Metaphysical Club , 2001 Researchers use this information to support the gateway drug theory — the hypothesis that using one intoxicating substance leads to future use of another. Jordy Byrd, The Pacific Northwest Inlander , 6 May 2015 Fox, the business and economics columnist for Time magazine, tells the story of the professors who enabled those abuses under the banner of the financial theory known as the efficient market hypothesis . Paul Krugman, The New York Times Book Review , 9 Aug. 2009

Incorrect Interpretations of "Theory"

Since this casual use does away with the distinctions upheld by the scientific community, hypothesis and theory are prone to being wrongly interpreted even when they are encountered in scientific contexts—or at least, contexts that allude to scientific study without making the critical distinction that scientists employ when weighing hypotheses and theories.

The most common occurrence is when theory is interpreted—and sometimes even gleefully seized upon—to mean something having less truth value than other scientific principles. (The word law applies to principles so firmly established that they are almost never questioned, such as the law of gravity.)

This mistake is one of projection: since we use theory in general use to mean something lightly speculated, then it's implied that scientists must be talking about the same level of uncertainty when they use theory to refer to their well-tested and reasoned principles.

The distinction has come to the forefront particularly on occasions when the content of science curricula in schools has been challenged—notably, when a school board in Georgia put stickers on textbooks stating that evolution was "a theory, not a fact, regarding the origin of living things." As Kenneth R. Miller, a cell biologist at Brown University, has said , a theory "doesn’t mean a hunch or a guess. A theory is a system of explanations that ties together a whole bunch of facts. It not only explains those facts, but predicts what you ought to find from other observations and experiments.”

While theories are never completely infallible, they form the basis of scientific reasoning because, as Miller said "to the best of our ability, we’ve tested them, and they’ve held up."

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Theory, Thesis, Hypothesis and the mysterious Theorem

lately I have been thinking about the terms theory, thesis, hypothesis and theorem. I am quite sure about the differences between a thesis and a hypothesis, but I did not really get what a theorem is. I would like to ask you to confirm my definition of each term or don' t. If you disagree with my definition, please explain why and give - if possible - a good example.

As an example I will use the axiom "Nothing is faster than light" of the Theory of Relativity.

Thesis : As far as I have figured out, a thesis is an assertion which a controversy is immanent to. So it needs a argumentative reasoning.

My first question, in reference to my example, is if every axiom is implicitly a thesis or not.

I am not sure about it, because if I took the axiom from the example, I would not know if there is any controversy about this assertion or if it is just an undisputed assertion, although there could be a controversy, because nobody can know if there is not something faster than light. On the other hand, if I have the assertion "There is a God", its clear to me that there will be a controversy. So it must be a thesis.

Further on I will assume the example axiom to be a thesis for further illustration.

Hypothesis : A hypothesis is a derived form of a thesis. It asserts a correlation between - at least - two factors (where a thesis is simply an assertion).

So in reference to the example I could derive the hypothesis "If there was something faster than light, then there would be a God" from my thesis "Nothing is faster than light". It asserts a correlation between the factors "speed of light" and "existence of a God" (although there is no causal relationship).

Theory: A theory is an abstract concept which tries to explain a discipline of reality. It consists of axioms/theses.

Theorem: This is something that I was not really able to figure out. I found a pattern in theoremes: It always seems to be based on some theory and tries to solve some paradoxon or other problem the theory has, but it does not change the theory at all. It is some lego that is put on the theory to fill a hole.

I don' t know if there is any truth in what I have written about the theoreme.

So I hope you can help me understanding :)

• terminology

• The words have different meaning in difference contexts, i.e. you don't prove theorems in physics you prove theories but a theory in physics is more like a conjecture in mathematics. A theorem is something that is proved deductively using logical reasoning or inference (think about what you do in a formal logical system like propositional logic). Mathematical theorems, like the fundamental theorem of arithmetic, are theorems because they can be proved in a completely deductive way. Physical laws are not proved deductively, they are proved inductively through observation and experiment. –  Not_Here Commented Jul 29, 2017 at 10:42
• From wikipedia's article on theorem: "In light of the requirement that theorems be proved, the concept of a theorem is fundamentally deductive, in contrast to the notion of a scientific law, which is experimental." In mathematics, conjectures are a lot more like scientific laws than theorems because they are things that we do not have a deductive proof for yet, but every test we've ever done to the conjecture came up positive. Consider Goldbach's conjecture, it is a conjecture because it doesn't have a proof yet, but we have yet to find a single counterexample, despite massive testing. –  Not_Here Commented Jul 29, 2017 at 10:44
• The biggest issue you're having, I think, is that you're mixing how the words are used in science and how they're used in math. Obviously there is over lap but the words have different meanings when they're used very strictly in those two contexts. For example, your definition of theory (besides the use of the term axioms because those also have different meanings in different contexts) is correct when applied to science but theory has a different definition in mathematical logic where it's a set of axioms and theorems in some formal language. –  Not_Here Commented Jul 29, 2017 at 10:51
• See if any of these definitions help you theorem , axiom , scientific hypotheses and scientific theories , mathematical conjecture , general statement of hypothesis that also touches on how its specifically used in mathematics . –  Not_Here Commented Jul 29, 2017 at 10:55

The biggest trouble that you will face when thinking about these ideas is that you are mixing terminology from two distinct fields into one. Some of those words are used very differently in science than they are in mathematics. It can become even more confusing when you consider how much math is used in science, but an explanation of how the words are used in their specific contexts will help illuminate the delineating line.

In mathematics, "thesis", "hypothesis", and "conjecture" are all used synonymously. From Wolfram's Mathworld:

Hypothesis: "A hypothesis is a proposition that is consistent with known data, but has been neither verified nor shown to be false." "In general mathematical usage, 'hypothesis' is roughly synonymous with 'conjecture.'" Conjecture: "A proposition which is consistent with known data, but has neither been verified nor shown to be false. It is synonymous with hypothesis."

Additionally, if you go to the disambiguation of the word "thesis" on wikipedia you see that in the subjects of mathematics and logic it links to "hypothesis" and "conjecture" as well. An example of a mathematical thesis is the Church-Turing thesis which, as you can see, is also sometimes called the Church-Turing conjecture and is described in that article as being a hypothesis. The reason that the Church-Turing thesis is a thesis is because it tries to take an informal idea (the idea of an algorithm) and give it a precise mathematical statement. Due to the fact that it starts with an informal idea, there isn't a purely deductive way to prove that the idea is true, therefore it's left open as a hypothesis and would be proven untrue if a counter example is shown.

As such, mathematical conjectures, theses, and hypotheses are statements in mathematics that seem probable and no counter example has yet been shown. This means that conjectures have yet to be proven , which delineates them from theorems.

A theorem is something that is not a conjecture, it is something that has been proven true. From Mathworld:

Theorem: "A theorem is a statement that can be demonstrated to be true by accepted mathematical operations and arguments. In general, a theorem is an embodiment of some general principle that makes it part of a larger theory. The process of showing a theorem to be correct is called a proof."

Examples of theorems are proven mathematical statements, things like the fundamental theorems of arithmetic , algebra , and calculus . Other, much simpler theorems, are things like the Pythagorean theorem . The picture of a theorem as something that solves a paradox or other problem is incorrect, a theorem is just a provably true statement. The Pythagorean theorem doesn't resolve a paradox in geometry, it is just a statement that has to be true, is provable, given the initial rules of geometry (the axioms).

Those are how the words are used in mathematics alone and in science they are sometimes used very differently. One important thing to understand is that science does not deal with theorems, scientific theories don't prove theorems. This is because science relies on inductive and abductive reasoning to learn about the world through empirical observation. A scientific theory is a general description of the world that is testable and has withstood repeated testing. In this way, they're usually made up out of scientific laws .

Scott Aaronson , a quantum information scientist who works on both fields, has highlighted the differences in the terminology on multiple occasions:

"I've learned from working in quantum information that there's a difference in terminology between fields. What mathematicians and computer scientists call a conjecture is typically what physicists would call a law." "I think my word is 'theorem'. It's something that you say is true and then you explain why it's true and then you put a box."

The context for the second quote is that Leonard Susskind asked Aaronson to explain a word from his mathematical background that people with a physics background might not understand or use in the same way. The reason everyone laughed is because the other physicists and computer scientists in the room understood how tongue in cheek Aaronson's pick for the word was: physics doesn't deal with theorems, in a mathematical sense, it deals with conjectures. That's why Susskind sarcastically says "A theorem, what's that?" And of course the "box" comment is a reference to what's put at the end of a proof of a theorem .

Ultimately, theorems are things that are deductively proven and as such exist in mathematics and logic. Theorems are used in science as well, you can use the Pythagorean theorem to help you solve a mechanics problem, but science doesn't prove theorems. Science tries to create theoretical models that help explain physical phenomena and those models can always be revised via new information. So if you are trying to apply the word theorem to a physical theory you are going to fail, the only parts of the physical theory that are theorems are the purely mathematical parts.

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What's the difference between "Hypothesis", "Thesis" and "Antithesis"? Please give a few examples to illustrate how they are different. Thank you.

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Z-test vs T-test: the differences and when to use each

What is hypothesis testing, what is a z-test, examples of a z-test, what is a t-test, examples of a t-test, how to know when to use z-test vs t-test, difference between z-test and t-test: a comparative table.

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Testing is how you determine effectiveness. Whether you work as a data scientist , statistician, or software developer, to ensure quality, you must measure performance. Without tests, you could deploy flawed code, features, or data points.

With that in mind, the use cases of testing are endless. Machine learning models need statistical tests. Data analysis involves statistical tests to validate assumptions. Optimization of any kind requires evaluation. You even need to test the strength of your hypothesis before you begin an inquiry.

Let's explore two inferential statistics: the Z-test vs the T-test. That way you can understand their differences, their unique purposes, and when to use a Z-test vs T-test.

To start, imagine you have a good idea. At the moment of inception, you have no data to back up your idea. It is an unformed thought. But the idea is an excellent starting point that can launch a full investigation. We consider this starting point a hypothesis.

But what if your hypothesis is off-base? You don’t want to dive into a full-scale search if it is a pointless chase with no reward. That is a waste of resources. You need to determine if you have a workable hypothesis.

Enter hypothesis testing. It is a statistical act used to assess the viability of a hypothesis. The method discovers whether there is sufficient data to support your idea. If there is next to no significance, you do not have a very plausible hypothesis.

To confirm the validity of a hypothesis, you compare it against the status quo (also known as the null hypothesis). Your idea is something new, opposite from normal conditions (also known as the alternative hypothesis). It is zero sum: only one hypothesis between the null and alternate hypothesis can be true in a given set of parameters.

In such a comparison test, you can now determine validity. You can compare and contrast conditions to find meaningful conclusions. Whichever conditions become statistically apparent determines which hypothesis is plausible.

A Z-test is a test statistic. It works with two groups: the sample mean and the population mean. It will test whether these two groups are different.

With a Z-test, you know the population standard deviation. That is to ensure statistical accuracy as you compare one group (the sample mean) vs the second group (the population mean). In other words, you can minimize external confounding factors with a normal distribution. In addition, a defining characteristic of a Z-test is that it works with large sample sizes (typically more than 30, so we achieve normal distribution as defined by the central limit theorem). These are two crucial criteria for using a Z-test.

Within hypothesis testing, your null hypothesis states there is no difference between the two groups your Z-test will compare. Your alternative hypothesis will state there is a difference that your Z-test will expose.

How to perform a Z-test

A Z-test occurs in the following standard format:

• Formulate your hypothesis: First, define the parameters of your alternative and null hypothesis.
• Choose a critical value: Second, determine what you consider a viable difference between your two groups. This threshold determines when you can say the null hypothesis should be rejected. Common levels are 0.01 (1%) or 0.05 (5%) , values found to best balance Type I and Type II errors .
• Collect samples: Obtain the needed data. The data must be large enough and random.
• Calculate for a Z-score: Input your data into the standard Z-test statistics formula, shown below, where Z = standard score, x = observed value, mu = mean of the sample, sigma = standard deviation of the sample .
• Compare: If the statistical test is greater than the critical value, you have achieved statistical significance. The sample mean is so different so you can reject the null hypothesis. Your alternative hypothesis (something other than the status quo) is at work, and that's worth investigating.

There are different variations of a Z-test. Let's explore examples of one-sample and two-sample Z-tests.

One-sample Z-test

A one-sample Z-test looks for either an increase or a decrease. There is one sample group involved, taken from a population. We want to see if there is a difference between those two means.

For example, consider a school principal who believes their students' IQ is higher than the state average. The state average is 100 points (population mean), give or take 20 (the population standard deviation). To prove this hypothesis, the principal takes 50 students (the sample size) and finds their IQ scores. To their delight, they earn an average of 110.

But does the difference offer any statistical value? The principal then plugs the numbers into a Z-test. Any Z-score greater than the critical value would state there is sufficient significance. The claim that the students have an above-average IQ is valid.

Two-sample Z-test

A two-sample test involves comparing the average of two sample groups against the population means. It is to determine a difference between two independent samples.

For example, our principal wants to compare their students' IQ scores to the school across the street. They believe their students' average IQ is higher. They don’t need to know the exact numerical increase or decrease. All they want is proof that their student's average scores are higher than the other group.

To confirm the validity of this hypothesis, the principal will search for statistical significance. They can take a 50-student sample size from their school and a 50-student sample size from the rival school. Now in possession of both sample group's average IQ (and the sample standard deviation), they hope to find a number value that is not equal. And they need them to be unequal by a significant amount.

If the test statistic comes in less than the critical value, the differences are negligible. There is not enough evidence to say the hypothesis is worth exploring, the null hypothesis is maintained. He would not have enough proof that the IQ levels between the two schools are different.

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A T-test performs the same crucial function as a Z-test: determine if there is a difference between the means of two groups. If there is a significant difference, you have achieved statistical validity for your hypothesis.

However, a T-test involves a different set of factors. Most importantly, a T-test applies when you do not know the sample variance of your values. You must generalize the normal distribution (or T-distribution). Plus, there is an expectation that you do not possess all the data in a given scenario.

These conditions better match reality, as it is often hard to collect data from entire populations or always obtain a standard normal distribution. That is why T-tests are more widely applicable than Z-tests, though they operate with less precision.

How to perform a T-test

A T-test occurs in the following standard format:

• Formulate your hypothesis: First, define the parameters of your null and alternative hypothesis.
• Choose a critical value: Like a Z-test, determine what you consider a viable difference between your two groups.
• Collect data: Obtain the needed data. One of the key differences is degrees of freedom in the samples of a T-test, so try to define the typical values and range of values in each group.
• Calculate your T-score: Input your data into the T-test formula you chose. Here is a one-sample formula:
• Compare: If the statistical test is greater than the critical value, you have achieved statistical significance. The sample mean is so far from the population mean that you likely have a useful hypothesis.

There are several different kinds of T-tests as well. Let's go through the standard one-sample and two-sample T-tests.

One-sample T-test

A one-sample T-test looks for an increase or decrease compared to a population mean.

For example, your company just went through sales training. Now, the manager wants to know if the training helped improve sales.

Previous company sales data shows an average of $100 on each transaction from all workers. The null hypothesis would be no change. The alternative hypothesis (which you hope is significant), is that there is an improvement.

To test if there is significance, you take the sales average of 20 salesmen. That is the only available data, and you have no other data from nationwide stores. The average of that sample of salesmen in the past month is $130. We will also assume that the standard deviation is approximately equal .

With this set of factors, you can calculate your T-score with a T-test. You compare the sample result to the critical value. In addition, you assess it against the number of degrees of freedom. Since we know with smaller sample data sizes there is greater uncertainty, we allow more room for our data to vary.

After comparing, we may find a lot of significance. That means the data possesses enough strength to support our hypothesis that sales training likely impacted sales. Of course, this is an estimate, as we only assessed one factor with a small group. Sales could have risen for numerous other reasons. But with our set of assumptions, our hypothesis is valid.

Two-sample T-test

A two-sample T-test occurs the same as a two-sample Z-test and compares if two groups are equal when compared to a defined population parameter.

For example, consider English and non-native speakers. We want to see the effect of maternal language on test scores inside a country. To do that, we will offer both groups a reading test and compare those scores to the average.

Of course, finding the mean of an entire population of language speakers is impossible to procure. Still, we can make some assumptions and compare them with a smaller size. We take 15 English speakers and 15 non-native speakers and collect their results. We can decide on a critical score value on the reading test as well. If the average score on the test is not crucially different or outside the population standard deviation, our assumption failed. There is no significant difference between the groups, so the impact of maternal language is not worth investigating.

Both a Z-test and a T-test validate a hypothesis. Both are parametric tests that rely on assumptions. The key difference between Z-test and T-test is in their assumptions (e.g. population variance).

Key differences about the data used result in different applications. You want to use the appropriate tool, otherwise you won’t draw valid conclusions from your data.

So when should you use a Z-test vs a T-test? Here are some factors to consider:

• Sample size: If the available sample size is small, opt for a T-test. Small sample sizes are more variable, so the greater spread of distribution and estimation of error involved with T-tests is ideal.
• Knowledge of the population standard deviation: Z-tests are more precise and often simpler to execute. So if you know the standard deviation, use a Z-test.
• Test purpose: If you are assessing the validity of a mean, a T-test is the best choice. If you are working with a hypothesized population proportion, go for a Z-test.
• Assumption of normality: A Z-test assumes a normal distribution. This does not apply to all real-world scenarios. If you hope to validate a hypothesis that is not well-defined, opt for a T-test instead.
• Type of data: You can only work within the constraints of the available data. The more information the better, but that is often not possible given testing and collecting conditions. If you have limited data describing means between groups, opt for a T-test. If you have large data sets comparing means between populations, you can use a Z-test.

Knowing the key differences with each statistical test makes selecting the right tool far easier. Here is a table that can help you compare:

Statistical testing lets you determine the validity of a hypothesis. You discover validity by determining if there is a significant difference between your hypothesis and the status quo. If there is, you have a possible idea worth exploring.

That process has numerous applications in the field of computer science and data analysis . You might want to determine the performance of an app with an A/B test. Or you might need to test if an application fits within the defined limits and compare performance metrics. Z-tests and T-tests can depict whether there is significant evidence in each of these scenarios. With that information, you can take the appropriate measures to fix bugs or optimize processes.

Z-test and T-test are helpful tools, especially for hypothesis testing. For data engineers of the future, knowledge of statistical testing will only help your work and overall career trajectory.

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