hypothesis making online

Hypothesis Maker Online

Looking for a hypothesis maker? This online tool for students will help you formulate a beautiful hypothesis quickly, efficiently, and for free.

Are you looking for an effective hypothesis maker online? Worry no more; try our online tool for students and formulate your hypothesis within no time.

• 🔎 How to Use the Tool?
• ⚗️ What Is a Hypothesis in Science?

👍 What Does a Good Hypothesis Mean?

• 🧭 Steps to Making a Good Hypothesis

🔗 References

📄 hypothesis maker: how to use it.

Our hypothesis maker is a simple and efficient tool you can access online for free.

If you want to create a research hypothesis quickly, you should fill out the research details in the given fields on the hypothesis generator.

Below are the fields you should complete to generate your hypothesis:

• Who or what is your research based on? For instance, the subject can be research group 1.
• What does the subject (research group 1) do?
• What does the subject affect? - This shows the predicted outcome, which is the object.
• Who or what will be compared with research group 1? (research group 2).

Once you fill the in the fields, you can click the ‘Make a hypothesis’ tab and get your results.

⚗️ What Is a Hypothesis in the Scientific Method?

A hypothesis is a statement describing an expectation or prediction of your research through observation.

It is similar to academic speculation and reasoning that discloses the outcome of your scientific test . An effective hypothesis, therefore, should be crafted carefully and with precision.

A good hypothesis should have dependent and independent variables . These variables are the elements you will test in your research method – it can be a concept, an event, or an object as long as it is observable.

You can observe the dependent variables while the independent variables keep changing during the experiment.

In a nutshell, a hypothesis directs and organizes the research methods you will use, forming a large section of research paper writing.

Hypothesis vs. Theory

A hypothesis is a realistic expectation that researchers make before any investigation. It is formulated and tested to prove whether the statement is true. A theory, on the other hand, is a factual principle supported by evidence. Thus, a theory is more fact-backed compared to a hypothesis.

Another difference is that a hypothesis is presented as a single statement , while a theory can be an assortment of things . Hypotheses are based on future possibilities toward a specific projection, but the results are uncertain. Theories are verified with undisputable results because of proper substantiation.

When it comes to data, a hypothesis relies on limited information , while a theory is established on an extensive data set tested on various conditions.

You should observe the stated assumption to prove its accuracy.

Since hypotheses have observable variables, their outcome is usually based on a specific occurrence. Conversely, theories are grounded on a general principle involving multiple experiments and research tests.

This general principle can apply to many specific cases.

The primary purpose of formulating a hypothesis is to present a tentative prediction for researchers to explore further through tests and observations. Theories, in their turn, aim to explain plausible occurrences in the form of a scientific study.

It would help to rely on several criteria to establish a good hypothesis. Below are the parameters you should use to analyze the quality of your hypothesis.

🧭 6 Steps to Making a Good Hypothesis

Writing a hypothesis becomes way simpler if you follow a tried-and-tested algorithm. Let’s explore how you can formulate a good hypothesis in a few steps:

Step #1: Ask Questions

The first step in hypothesis creation is asking real questions about the surrounding reality.

Why do things happen as they do? What are the causes of some occurrences?

Your curiosity will trigger great questions that you can use to formulate a stellar hypothesis. So, ensure you pick a research topic of interest to scrutinize the world’s phenomena, processes, and events.

Step #2: Do Initial Research

Carry out preliminary research and gather essential background information about your topic of choice.

The extent of the information you collect will depend on what you want to prove.

Your initial research can be complete with a few academic books or a simple Internet search for quick answers with relevant statistics.

Still, keep in mind that in this phase, it is too early to prove or disapprove of your hypothesis.

Step #3: Identify Your Variables

Now that you have a basic understanding of the topic, choose the dependent and independent variables.

Take note that independent variables are the ones you can’t control, so understand the limitations of your test before settling on a final hypothesis.

Step #4: Formulate Your Hypothesis

You can write your hypothesis as an ‘if – then’ expression . Presenting any hypothesis in this format is reliable since it describes the cause-and-effect you want to test.

For instance: If I study every day, then I will get good grades.

Step #5: Gather Relevant Data

Once you have identified your variables and formulated the hypothesis, you can start the experiment. Remember, the conclusion you make will be a proof or rebuttal of your initial assumption.

So, gather relevant information, whether for a simple or statistical hypothesis, because you need to back your statement.

Step #6: Record Your Findings

Finally, write down your conclusions in a research paper .

Outline in detail whether the test has proved or disproved your hypothesis.

Edit and proofread your work, using a plagiarism checker to ensure the authenticity of your text.

We hope that the above tips will be useful for you. Note that if you need to conduct business analysis, you can use the free templates we’ve prepared: SWOT , PESTLE , VRIO , SOAR , and Porter’s 5 Forces .

❓ Hypothesis Formulator FAQ

Updated: Jul 19th, 2024

• How to Write a Hypothesis in 6 Steps - Grammarly
• Forming a Good Hypothesis for Scientific Research
• The Hypothesis in Science Writing
• Scientific Method: Step 3: HYPOTHESIS - Subject Guides
• Hypothesis Template & Examples - Video & Lesson Transcript
• Free Essays
• Writing Tools
• Lit. Guides
• Donate a Paper
• Q&A by Experts
• Referencing Guides
• Free Textbooks
• Tongue Twisters
• Editorial Policy
• Job Openings
• Video Contest
• Writing Scholarship
• Discount Codes
• Brand Guidelines
• IvyPanda Shop
• Online Courses
• Terms and Conditions
• Privacy Policy
• Cookies Policy
• Copyright Principles
• DMCA Request
• Service Notice

IvyPanda's free online hypothesis maker will help you formulate a hypothesis for your study. With this easy-to-use tool, you just need to provide basic info about the focus of your research, its variables, and predicted outcomes. The rest is on us. Get a perfect hypothesis fast!

Hypothesis Maker

The best free AI hypothesis maker to master the art of hypothesis creation with ease. Generate high-quality and accurate hypotheses in minutes.

• Authoritative
• Conservative
• Conversational
• Enthusiastic
• Informative
• Inspirational
• Journalistic
• Matteroffact
• Professional
• Provocative
• Sympathetic
• Trustworthy
• Unapologetic
• Authoritative Pro
• Cheerful Pro
• Conservative Pro
• Conversational Pro
• Convincing Pro
• Creative Pro
• Enthusiastic Pro
• Expository Pro
• Friendly Pro
• Humorous Pro
• Informative Pro
• Inspirational Pro
• Irreverent Pro
• Journalistic Pro
• Matteroffact Pro
• Nostalgic Pro
• Objective Pro
• Passionate Pro
• Playful Pro
• Professional Pro
• Provocative Pro
• Respectful Pro
• Romantic Pro
• Sarcastic Pro
• Serious Pro
• Subjective Pro
• Sympathetic Pro
• Thoughtful Pro
• Trustworthy Pro
• Unapologetic Pro
• Worried Pro
• English (US)
• German (Germany)
• Italian (Italy)
• Japanese (Japan)
• Russian (Russia)
• Portuguese (Portugal)
• Hindi (India)
• Urdu (Pakistan)
• Arabic (Saudi Arabia)
• French (France)
• English (UK)
• English (Australia)
• English (Canada)
• English (India)
• English (Singapore)
• English (New Zealand)
• English (South Africa)
• Spanish (Spain)
• Spanish (Mexico)
• Spanish (United States)
• Arabic (Egypt)
• Arabic (United Arab Emirates)
• Arabic (Kuwait)
• Arabic (Bahrain)
• Arabic (Qatar)
• Arabic (Oman)
• Arabic (Jordan)
• Arabic (Lebanon)
• Danish (Denmark)
• German (Switzerland)
• German (Austria)
• French (Canada)
• French (Switzerland)
• French (Belgium)
• Italian (Switzerland)
• Dutch (Netherlands)
• Dutch (Belgium)
• Portuguese (Brazil)
• Chinese (China)
• Chinese (Taiwan)
• Chinese (Hong Kong)
• Chinese (Singapore)
• Korean (South Korea)
• Finnish (Finland)
• Greek (Greece)
• Czech (Czech Republic)
• Swedish (Sweden)
• Norwegian (Norway)
• Turkish (Turkey)
• Polish (Poland)
• Romanian (Romania)
• Hungarian (Hungary)
• Thai (Thailand)
• Hebrew (Israel)
• Indonesian (Indonesia)
• Vietnamese (Vietnam)
• Malay (Malaysia)
• Tagalog (Philippines)
• Swahili (Kenya)
• Swahili (Tanzania)
• Zulu (South Africa)
• Xhosa (South Africa)
• Amharic (Ethiopia)
• Tamil (India)
• Tamil (Sri Lanka)
• Bengali (Bangladesh)
• Bengali (India)
• Punjabi (Pakistan)
• Punjabi (India)
• Marathi (India)
• Telugu (India)
• Kannada (India)
• Gujarati (India)
• Oriya (India)
• Malayalam (India)
• Urdu (India)
• Persian (Iran)
• Azerbaijani (Azerbaijan)
• Ukrainian (Ukraine)
• Belarusian (Belarus)
• Catalan (Spain)
• Basque (Spain)
• Galician (Spain)
• Slovak (Slovakia)
• Lithuanian (Lithuania)
• Latvian (Latvia)
• Estonian (Estonia)
• Bulgarian (Bulgaria)
• Albanian (Albania)
• Croatian (Croatia)
• Slovenian (Slovenia)
• Bosnian (Bosnia and Herzegovina)
• Serbian (Serbia)
• Macedonian (North Macedonia)
• Montenegrin (Montenegro)
• Maltese (Malta)
• Irish (Ireland)
• Welsh (United Kingdom)
• Scots Gaelic (United Kingdom)
• Icelandic (Iceland)
• Luxembourgish (Luxembourg)
• Afrikaans (South Africa)
• Hausa (Nigeria)
• Yoruba (Nigeria)
• Somali (Somalia)
• Tigrinya (Eritrea)
• Kinyarwanda (Rwanda)
• Sesotho (Lesotho)
• Shona (Zimbabwe)
• Sinhala (Sri Lanka)
• Dhivehi (Maldives)
• Burmese (Myanmar)
• Khmer (Cambodia)
• Mongolian (Mongolia)
• Tibetan (China)
• Uighur (China)
• Pashto (Afghanistan)
• Dari (Afghanistan)
• Nepali (Nepal)
• Dzongkha (Bhutan)
• Sesotho (South Africa)
• Setswana (Botswana)
• Seselwa Creole (Seychelles)
• Mauritian Creole (Mauritius)
• Haitian Creole (Haiti)
• Greenlandic (Greenland)
• Faroese (Faroe Islands)
• Samoan (Samoa)
• Tongan (Tonga)
• English (UK) Pro -->
• English (Australia) Pro -->
• English (Canada) Pro -->
• English (India) Pro -->
• English (Singapore) Pro -->
• English (New Zealand) Pro -->
• English (South Africa) Pro -->
• Spanish (Spain) Pro -->
• Spanish (Mexico) Pro -->
• Spanish (United States) Pro -->
• Arabic (Egypt) Pro -->
• Arabic (United Arab Emirates) Pro -->
• Arabic (Kuwait) Pro -->
• Arabic (Bahrain) Pro -->
• Arabic (Qatar) Pro -->
• Arabic (Oman) Pro -->
• Arabic (Jordan) Pro -->
• Arabic (Lebanon) Pro -->
• Danish (Denmark) Pro -->
• German (Switzerland) Pro -->
• German (Austria) Pro -->
• French (Canada) Pro -->
• French (Switzerland) Pro -->
• French (Belgium) Pro -->
• Italian (Switzerland) Pro -->
• Dutch (Netherlands) Pro -->
• Dutch (Belgium) Pro -->
• Portuguese (Brazil) Pro -->
• Chinese (China) Pro -->
• Chinese (Taiwan) Pro -->
• Chinese (Hong Kong) Pro -->
• Chinese (Singapore) Pro -->
• Korean (South Korea) Pro -->
• Finnish (Finland) Pro -->
• Greek (Greece) Pro -->
• Czech (Czech Republic) Pro -->
• Swedish (Sweden) Pro -->
• Norwegian (Norway) Pro -->
• Turkish (Turkey) Pro -->
• Polish (Poland) Pro -->
• Romanian (Romania) Pro -->
• Hungarian (Hungary) Pro -->
• Thai (Thailand) Pro -->
• Hebrew (Israel) Pro -->
• Indonesian (Indonesia) Pro -->
• Vietnamese (Vietnam) Pro -->
• Malay (Malaysia) Pro -->
• Tagalog (Philippines) Pro -->
• Swahili (Kenya) Pro -->
• Swahili (Tanzania) Pro -->
• Zulu (South Africa) Pro -->
• Xhosa (South Africa) Pro -->
• Amharic (Ethiopia) Pro -->
• Tamil (India) Pro -->
• Tamil (Sri Lanka) Pro -->
• Bengali (Bangladesh) Pro -->
• Bengali (India) Pro -->
• Punjabi (Pakistan) Pro -->
• Punjabi (India) Pro -->
• Marathi (India) Pro -->
• Telugu (India) Pro -->
• Kannada (India) Pro -->
• Gujarati (India) Pro -->
• Oriya (India) Pro -->
• Malayalam (India) Pro -->
• Urdu (India) Pro -->
• Persian (Iran) Pro -->
• Azerbaijani (Azerbaijan) Pro -->
• Ukrainian (Ukraine) Pro -->
• Belarusian (Belarus) Pro -->
• Catalan (Spain) Pro -->
• Basque (Spain) Pro -->
• Galician (Spain) Pro -->
• Slovak (Slovakia) Pro -->
• Lithuanian (Lithuania) Pro -->
• Latvian (Latvia) Pro -->
• Estonian (Estonia) Pro -->
• Bulgarian (Bulgaria) Pro -->
• Albanian (Albania) Pro -->
• Croatian (Croatia) Pro -->
• Slovenian (Slovenia) Pro -->
• Bosnian (Bosnia and Herzegovina) Pro -->
• Serbian (Serbia) Pro -->
• Macedonian (North Macedonia) Pro -->
• Montenegrin (Montenegro) Pro -->
• Maltese (Malta) Pro -->
• Irish (Ireland) Pro -->
• Welsh (United Kingdom) Pro -->
• Scots Gaelic (United Kingdom) Pro -->
• Icelandic (Iceland) Pro -->
• Luxembourgish (Luxembourg) Pro -->
• Afrikaans (South Africa) Pro -->
• Hausa (Nigeria) Pro -->
• Yoruba (Nigeria) Pro -->
• Somali (Somalia) Pro -->
• Tigrinya (Eritrea) Pro -->
• Kinyarwanda (Rwanda) Pro -->
• Sesotho (Lesotho) Pro -->
• Shona (Zimbabwe) Pro -->
• Sinhala (Sri Lanka) Pro -->
• Dhivehi (Maldives) Pro -->
• Burmese (Myanmar) Pro -->
• Lao (Laos) Pro -->
• Khmer (Cambodia) Pro -->
• Mongolian (Mongolia) Pro -->
• Tibetan (China) Pro -->
• Uighur (China) Pro -->
• Pashto (Afghanistan) Pro -->
• Dari (Afghanistan) Pro -->
• Nepali (Nepal) Pro -->
• Dzongkha (Bhutan) Pro -->
• Sesotho (South Africa) Pro -->
• Setswana (Botswana) Pro -->
• Seselwa Creole (Seychelles) Pro -->
• Mauritian Creole (Mauritius) Pro -->
• Haitian Creole (Haiti) Pro -->
• Greenlandic (Greenland) Pro -->
• Faroese (Faroe Islands) Pro -->
• Samoan (Samoa) Pro -->
• Tongan (Tonga) Pro -->

Why Choose Hypothesis-Maker?

Unlock the potential of your research with Hypothesis-Maker. This tool is designed to help you generate clear, concise, and compelling hypotheses for any type of research.

• Formulate hypotheses that set a strong foundation for your research.
• Save time by generating hypotheses quickly and efficiently.
• Tailor the hypotheses to align with your specific research goals and methodologies.

How Does Hypothesis-Maker Work?

Simplify the hypothesis creation process with Hypothesis-Maker. Follow these simple steps to generate effective hypotheses:

1. Provide Your Input

Enter your value in the input box. The AI will interpret the input within the given context.

2. Generate

Click the "Generate" button to craft a compelling and well-structured response.

Use Cases of Hypothesis-Maker

Explore how Hypothesis-Maker can enhance your research across various fields and formats. Whether you're conducting scientific research, social studies, business analysis, or academic projects, this tool can help you create hypotheses that drive your research forward.

Scientific Research Develop hypotheses that guide your experiments and investigations. Hypothesis-Maker helps you outline clear and testable statements that can be empirically evaluated, ensuring your research is grounded in a solid theoretical framework.

Social Studies Generate hypotheses that address social phenomena and human behavior. The tool assists in formulating hypotheses that are relevant, significant, and researchable within the context of social sciences.

Business Analysis Create hypotheses that inform your business strategies and decisions. Use Hypothesis-Maker to develop statements that can be tested through market research, consumer behavior studies, and financial analyses.

Academic Projects Strengthen your academic writing with well-crafted hypotheses. Whether for theses, dissertations, or research papers, Hypothesis-Maker ensures your hypotheses are clear, concise, and aligned with your research questions.

Who Benefits from Hypothesis-Maker?

From researchers, analysts, to students, everyone can benefit from the Hypothesis-Maker tool.

Researchers For researchers, Hypothesis-Maker can help streamline the hypothesis formulation process, allowing you to focus more on data collection and analysis. By using this tool, you can ensure that your research is based on strong, testable hypotheses.

Analysts Enhance your analytical projects with robust hypotheses. Hypothesis-Maker helps analysts in fields like finance, marketing, and data science to develop hypotheses that guide their investigations and support data-driven decision-making.

Students Improve your academic research and writing skills with Hypothesis-Maker. This tool is particularly useful for students who are new to hypothesis formulation, providing guidance and support in creating strong and researchable statements for their projects and assignments.

Error message

Boost your productivity & creativity!

• 500+ tools to spark your creativity.
• 100+ languages, conquer the globe.
• 20+ tones & styles, find your perfect brand voice.
• No document or input limits, write forever!
• Priority support & early access to new features!
• Limited-time offer

Still hesitant? We offer 7-Day Money-Back Guarantee Without Question.

Elevate Every Aspect of Your Work

LogicBalls combines brainstorming, writing, analysis, and research in one powerful AI tool. Enhance your professional content now!

• Pricing Lightweight Script Blog
• Sign Up Log In

AI Hypothesis Generator

Hypothesis Generator to help you come up with a boilerplate hypothesis for your test ideas. Generate well-structured hypothesis in under 10 seconds!

1. Give us a brief about your hypothesis...

Hypotheses in A/B Testing

Hypotheses form an integral part of A/B Testing. They provide a clear path and expected outcome for the test, based on the initial conditions, such as the user interface and user experience, among others. A well-defined hypothesis is the foundation of any successful A/B test, guiding the direction of the test and serving as a benchmark against which the test’s results are evaluated.

What are the benefits?

The Automated Hypothesis Creator simplifies the first step in the A/B testing process and provides several benefits:

• Quick and efficient hypothesis generation.
• Saves time and resources which can often be invested in analysing the output of the A/B test.
• Provides insightful and scientifically-backed predictions.
• Outlines a clear picture for the A/B test, thus leading to more accurate outcomes.

How to Use it with A/B Testing?

To use the Automated Hypothesis Creator with A/B testing, follow these simple steps:

• Begin by clearly formulating your query.
• Use the text area in the tool to provide the necessary input data.
• Click the “Create Hypothesis” button.
• Wait for a while for the tool to process your request and generate a hypothesis.
• Once the hypothesis is created, use it as a basis for your A/B test.

Try other free tools:

• A/B Test Headline Generator
• Sample Size Calculator
• A/B Test Duration Calculator
• Statistical Significance Calculator

A/B testing platform for people who care about   website performance

Mida is 10X faster than everything you have ever considered. Try it yourself.

Mida.so is a super lightweight A/B testing tool to help you experiment, analyze and implement conversion strategies in minutes.

You are using an outdated browser. Please upgrade your browser to improve your experience (and have this site working as it suppose).

Create your rock solid experiment hypothesis

A. fill out the form  , b. your hypothesis will appear here, why should you use this method.

Hypotheses give good test results, simple as that. Use our tool to get structure in how to formulate your hypotheses.

You could use it as a kind of "bullshit detector" - if your hypothesis doesn’t fit into the template it's probably not a good testing hypothesis.

A good hypothesis is a multi-stage rocket - IAR

• Insights - What have you noticed that makes you think that you have to make a change?
• Action - What will you do?
• Results - What do you want to accomplish and how do you measure it?

Get in touch with us

♥ from the Conversionista! team | Report a bug or an issue

• Argumentative
• Ecocriticism
• Informative
• Explicatory
• Illustrative
• Problem Solution
• Interpretive
• Music Analysis
• All Essay Examples
• Entertainment
• Law, Crime & Punishment
• Artificial Intelligence
• Environment
• Geography & Travel
• Government & Politics
• Nursing & Health
• Information Science and Technology
• All Essay Topics

Online Hypothesis Generator

Forge precise, research-backed hypotheses in a snap using our top-notch hypothesis creator, ensuring your study starts on solid ground..

How to Create a Solid & Precise Hypothesis with EssayGPT?

Ever wondered how to come up with a hypothesis that's both detailed and relevant? Kick-start your research endeavors with EssayGPT's hypothesis generator by these steps:

• 1. Start by by indicating the positive or negative trajectory of your hypothesis in the "Effect" section.
• 2. Then, enter specifics of the experimental group in the "Who (what)" field.
• 3. Contrast the experimental group against its counterpart by detailing the control group in the appropriate section.
• 4. Pinpoint the element of study you're measuring by populating the "The measured thing is" field.
• 5. Choose between GPT 3.5 or GPT 4, and hit 'Generate' for your AI-empowered hypotheses.

Try Our Other Powerful AI Products

Bypass AI detection with 100% undetectable AI content

Create undetectable, plagiarism-free essays with accurate citations

Solve ANY homework problem with a smart AI. 99% accuracy guaranteed.

Browser Extension

The all-in-one ChatGPT copilot: rewrite, translate, summarize, Chat with PDF anywhere

Why EssayGPT's Hypothesis Creator Stands Above the Rest?

Embarking on a research venture necessitates precision, clarity, and an unwavering commitment to reliability. EssayGPT  promises all of this and more, setting itself far apart from the competition.

Let’s dive into the unparalleled features of our hypothesis generator:

AI-Powered Precision: Central to the EssayGPT's hypothesis generator is an avant-garde AI framework. This ensures every hypothesis generated is data-driven, accurate, and aligns with your specified parameters.

Swift, On-Point Outputs: Time is of the essence in research. EssayGPT's hypothesis generator pledges quick turnarounds, without compromising the quality and relevance of the generated hypotheses.

Diverse Subject Mastery: From social sciences to intricate physics postulations, EssayGPT's hypothesis generator extends its prowess across a plethora of disciplines, ensuring your topic, no matter how niche, finds its rightful hypothesis.

A Breeze of Usability: Ditch convoluted interfaces. EssayGPT's hypothesis generator boasts an intuitive design for all users, making hypothesis crafting as effortless as a couple of clicks.

Key Steps on Writing Proper Research Hypothesis with EssayGPT

Tapping into the potential of EssayGPT's hypothesis generator can revolutionize your research process. However, to optimize the AI's capabilities, a few key considerations can significantly enhance the coherence and relevance of the generated hypotheses.

Here's a deeper dive into those nuances.

Precision in Input: The tool's prowess lies in its ability to interpret and process the information it's given. Just as a finely tuned instrument delivers the best music, clear and specific inputs allow the generator to produce accurate hypotheses. Being vague or too broad might lead to generic outcomes that don’t precisely serve your research aims.

Alignment with Research Context: The essence of a valuable hypothesis is its seamless fit within the broader research landscape. It's not just about a statement, but one that directly speaks to, and illuminates, the research problem or question you're addressing. By ensuring that the generated hypothesis aligns contextually, you guarantee its relevance and applicability.

Vocabulary Matters: Each field of study has its lexicon. Incorporating field-specific terms or jargon can transform a generic statement into a specialized hypothesis. It’s not just about linguistic accuracy, but about imbuing your hypothesis with the depth and resonance pertinent to your study's discipline.

The Human Element: AI is a powerful tool, but it's the human touch that brings depth, intuition, and context. After the AI crafts the hypothesis, it's beneficial to weave in personal insights or adjust nuances. This ensures that while the hypothesis is technically sound, it also captures the unique intricacies and flavors of individual research endeavors.

Iconic Features of EssayGPT's Hypothesis Maker at a Glance

Check Out Other Powerful AI Tools Just Like This Hypothesis Generator

Thesis statement generator, essay checker, essay rewriter, essay hook generator, essay extender, essay introduction generator, essay outline generator, free essay conclusion generator, essay shortener, dive into a world of inspiration.

• A Brief History of Playboy Enterprises
• Kurt Lewin ( 1947 ) Divides The Change Process Essay
• Individualism Essay
• Bigfoot Is Not Real
• The 1972 Munich Olympics Hostage Crisis Essay
• Persuasive Essay On Silent Spring
• Analyse The Size And Scope Of The Global Tourism And Hospitality Industry
• Summary: The Pregnancy Pact
• Loss Of Faith In Maus By Vladek
• Character Analysis Of Nancy Wheeler In Stranger Things
• External and Internal Factors Essay
• Persuasive Letter
• Stovall V. Denno 388 US
• Baroque Economy
• What Is The Mood Of The Metamorphosis By Franz Kafka
• Essay on Karen Horney V. Alfred Adler

1. Can EssayGPT's hypothesis creator tackle complex and multidimensional topics?

Absolutely. The hypothesis creator harnesses a state-of-the-art AI algorithm, expertly designed to navigate even the most complex and multidimensional subjects. Leveraging advanced contextual comprehension coupled with vast datasets, the tool is adept at crafting accurate hypotheses irrespective of topic intricacy.

2. Are users expected to incur any costs when using EssayGPT's Hypothesis maker?

The basic version of the hypothesis generator is free and permits users to generate content up to 3,000 words per week. For users requiring more extensive capabilities, we offer subscription plans that provide increased word limits and access to our advanced content generation features.

3. Does the EssayGPT hypothesis generator offer support for multiple languages?

Certainly! EssayGPT's esteemed hypothesis generator is linguistically versatile, offering compatibility with an impressive roster of over 30 languages. This ensures that your research endeavors remain unhindered, irrespective of the language of preference.

4. How does EssayGPT's hypothesis generator ensure the uniqueness of the generated hypothesis?

Ensuring that your hypotheses are both pristine and unparalleled is at the heart of EssayGPT's ethos. To this end, our hypothesis generator taps into cutting-edge language models to ensure that every hypothesis sculpted retains an aura of unmatched originality.

Use Our Hypothesis Generator to Power Your Research Journey

Try EssayGPT's Hypothesis Generator to explore new frontiers. Formulate testable hypotheses to supercharge your research!

Research Hypothesis Generator Online

• ️👍 Hypothesis Maker: the Benefits
• ️🔎 How to Use the Tool?
• ️🕵️ What Is a Research Hypothesis?
• ️⚗️ Scientific Method
• ️🔗 References

👍 Hypothesis Maker: the Benefits

Here are the key benefits of this null and alternative hypothesis generator.

🔎 Hypothesis Generator: How to Use It?

Whenever you conduct research, whether a 5-paragraph essay or a more complex assignment, you need to create a hypothesis for this study.

Clueless about how to create a good hypothesis?

No need to waste time and energy on this small portion of your writing process! You can always use our hypothesis creator to get a researchable assumption in no time.

To get a ready-made hypothesis idea, you need to:

• State the object of your study
• Specify what the object does
• Lay out the outcome of that activity
• Indicate the comparison group

Once all data is inserted into the fields, you can press the “Generate now” button and get the result from our hypothesis generator for research paper or any other academic task.

🕵️ What Is a Research Hypothesis?

A hypothesis is your assumption based on existing academic knowledge and observations of the surrounding natural world.

It also involves a healthy portion of intuition because you should arrive at an interesting, commonsense question about the phenomena or processes you observe.

The traditional formula for hypothesis generation is an “if…then” statement, reflecting its falsifiability and testability.

What do these terms mean?

• Testability means you can formulate a scientific guess and test it with data and analysis.
• Falsifiability is a related feature, allowing you to refute the hypothesis with data and show that your guess has no tangible support in real-world data.

For example, you might want to hypothesize the following:

If children are given enough free play time, their intelligence scores rise quicker.

You can test this assumption by observing and measuring two groups – children involved in much free play and those who don’t get free play time. Once the study period ends, you can measure the intelligence scores in both groups to see the difference, thus proving or disproving your hypothesis, which will be testing your hypothesis. If you find tangible differences between the two groups, your hypothesis will be proven, and if there is no difference, the hypothesis will prove false.

Null and Alternative Hypothesis

As a rule, hypotheses are presented in pairs in academic studies, as your scientific guess may be refuted or proved. Thus, you should formulate two hypotheses – a null and alternative variant of the same guess – to see which one is proved with your experiment.

The alternative hypothesis is formulated in an affirmative form, assuming a specific relationship between variables. In other words, you hypothesize that the predetermined outcome will be observed if one condition is met.

Watching films before sleep reduces the quality of sleep.

The null hypothesis is formulated in a negative form, suggesting that there is no association between the variables of your interest. For example:

Watching films before sleep doesn’t affect the quality of sleep.

⚗️ Creating a Hypothesis: the Key Steps

The development and testing of multiple hypotheses are the basis of the scientific method .

Without such inquiries, academic knowledge would never progress, and humanity would remain with a limited understanding of the natural world.

How can you contribute to the existing academic base with well-developed and rigorously planned scientific studies ? Here is an introduction to the empirical method of scientific inquiry.

Step #1: Observe the World Around You

Look around you to see what’s taking place in your academic area. If you’re a biology researcher, look into the untapped biological processes or intriguing facts that nobody has managed to explain before you.

What’s surprising or unusual in your observations? How can you approach this area of interest?

That’s the starting point of an academic journey to new knowledge.

Step #2: Ask Questions

Now that you’ve found a subject of interest, it’s time to generate scientific research questions.

A question can be called scientific if it is well-defined, focuses on measurable dimensions, and is largely testable.

Some hints for a scientific question are:

• What effect does X produce on Y?
• What happens if the intensity of X’s impact reduces or rises?
• What is the primary cause of X?
• How is X related to Y in this group of people?
• How effective is X in the field of C?

As you can see, X is the independent variable , and Y is the dependent variable.

This principle of hypothesis formulation is vital for cases when you want to illustrate or measure the strength of one variable’s effect on the other.

Step #3: Generate a Research Hypothesis

After asking the scientific question, you can hypothesize what your answer to it can be.

You don’t have any data yet to answer the question confidently, but you can assume what effect you will observe during an empirical investigation.

For example, suppose your background research shows that protein consumption boosts muscle growth.

In that case, you can hypothesize that a sample group consuming much protein after physical training will exhibit better muscle growth dynamics compared to those who don’t eat protein. This way, you’re making a scientific guess based on your prior knowledge of the subject and your intuition.

Step #4: Hold an Experiment

With a hypothesis at hand, you can proceed to the empirical study for its testing. As a rule, you should have a clearly formulated methodology for proving or disproving your hypothesis before you create it. Otherwise, how can you know that it is testable? An effective hypothesis usually contains all data about the research context and the population of interest.

For example:

Marijuana consumption among U. S. college students reduces their motivation and academic achievement.

• The study sample here is college students.
• The dependent variable is motivation and academic achievement, which you can measure with any validated scale (e.g., Intrinsic Motivation Inventory).
• The inclusion criterion for the study’s experimental group is marijuana use.
• The control group might be a group of marijuana non-users from the same population.
• A viable research methodology is to ask both groups to fill out the survey and compare the results.

Step #5: Analyze Your Findings

Once the study is over and you have the collected dataset, it’s time to analyze the findings.

The methodology should also delineate the criteria for proving or disproving the hypothesis.

Using the previous section’s example, your hypothesis is proven if the experimental group reveals lower motivational scores and has a lower GPA . If both groups’ motivation and GPA scores aren’t statistically different, your hypothesis is false.

Step #6: Formulate Your Conclusion

Using your study’s hypothesis and outcomes, you can now generate a conclusion . If the alternative hypothesis is proven, you can conclude that marijuana use hinders students’ achievement and motivation. If the null hypothesis is validated, you should report no identified relationship between low academic achievement and weed use.

Thank you for reading this article! Note that if you need to conduct a business analysis, you can try our free tools: SWOT , VRIO , SOAR , PESTEL , and Porter’s Five Forces .

❓ Research Hypothesis Generator FAQ

❓ what is a research hypothesis.

A hypothesis is a guess or assumption you make by looking at the available data from the natural world. You assume a specific relationship between variables or phenomena and formulate that supposition for further testing with experimentation and analysis.

❓ How to write a hypothesis?

To compose an effective hypothesis, you need to look at your research question and formulate a couple of ways to answer it. The available scientific data can guide you to assume your study’s outcome. Thus, the hypothesis is a guess of how your research question will be answered by the end of your research.

❓ What is the difference between prediction and hypothesis?

A prediction is your forecast about the outcome of some activities or experimentation. It is a guess of what will happen if you perform some actions with a specific object or person. A hypothesis is a more in-depth inquiry into the way things are related. It is more about explaining specific mechanisms and relationships.

❓ What makes a good hypothesis?

A strong hypothesis should indicate the dependent and independent variables, specifying the relationship you assume between them. You can also strengthen your hypothesis by indicating a specific population group, an intervention period, and the context in which you’ll hold the study.

Updated: Aug 23rd, 2024

🔗 References

• What is and How to Write a Good Hypothesis in Research?
• Research questions, hypotheses and objectives – PMC – NCBI
• Developing the research hypothesis – PubMed
• Alternative Hypothesis – SAGE Research Methods
• Alternative Hypothesis Guide: Definition, Types and Examples

Hypothesis Generator

Write about, want some more features.

• - History to store generated content
• - Access to mobile apps for content generation on the go
• - Access to 500+ other AI tools and templates

Exploring the AI4Chat Hypothesis Generator

An overview.

AI4Chat's Hypothesis Generator is a cutting-edge tool that fosters innovation and creativity in problem-solving and research. With just a click, this feature presents unique and perceptive hypothesis, enabling users to delve deeper into their field of interest.

Functionality and Application

The Hypothesis Generator is embedded within the AI4Chat platform, functioning as a cognitive assistive tool. By interrelating complex variables within specified parameters, the generator can derive novel and significant hypotheses. It plays an indispensable role in various fields, benefiting researchers, students, scientists, and problem-solvers, to generate insights and streamline decision-making processes.

Integrated Features

AI4Chat's Hypothesis Generator also boasts integrated features such as chat synchronization across all devices, labels, categories, notes, chat description, search, and dark mode. These features enhance the user experience by offering convenient and efficient tools that simplify the hypothesis generation process.

Accessibility and User Interface

AI4Chat strives for accessibility and ease of use, offering the Hypothesis Generator on its mobile applications for Android and iOS as well as its website. With a user-friendly interface, navigating through the features and tools becomes effortless. The dark mode feature allows for a comfortable viewing experience, making hypothesis generation an intuitive process.

Questions about AI4Chat? We are here to help!

For any inquiries, drop us an email at [email protected] . We’re always eager to assist and provide more information.

What Is AI4Chat?

What features are available on ai4chat.

• 🔍 Google Search Results: Generate content that's current and fact-based using Google's search results.
• 📂 Categorizing Chats into Folders: Organize your chats for easy access and management.
• 🏷 Adding Labels: Tag your chats for quick identification and sorting.
• 📷 Custom Chat Images: Set a custom image for each chat, personalizing your chat interface.
• 🔢 Word Count: Monitor the length of your chats with a word count feature.
• 🎨 Tone Selection: Customize the tone of chatbot responses to suit the mood or context of the conversation.
• 📝 Chat Description: Add descriptions to your chats for context and clarity, making it easier to revisit and understand chat histories.
• 🔎 Search: Easily find past chats with a powerful search feature, improving your ability to recall information.
• 🔗 Sharable Chat Link: Generate a link to share your chat, allowing others to view the conversation.
• 🌍 Multilingual Chat in 75+ Languages: Communicate and generate content in over 75 languages, expanding your global reach.
• 💻 AI Code Assistance: Leverage AI to generate code in any programming language, debug errors, or ask any coding-related questions. Our AI models are specially trained to understand and provide solutions for coding queries, making it an invaluable tool for developers seeking to enhance productivity, learn new programming concepts, or solve complex coding challenges efficiently.
• 📁 AI Chat with Files and Images: Upload images or files and ask questions related to their content. AI automatically understands and answers questions based on the content or context of the uploaded files.
• 📷 AI Text to Image & Image to Image: Create stunning visuals with models like Stable Diffusion, Midjourney, DALLE v2, DALLE v3, and Leonardo AI.
• 🎙 AI Text to Voice/Speech: Transform text into engaging audio content.
• 🎵 AI Text to Music: Convert your text prompts into melodious music tracks. Leverage the power of AI to craft unique compositions based on the mood, genre, or theme you specify in your text.
• 🎥 AI Text to Video: Convert text scripts into captivating video content.
• 🔍 AI Image to Text with Context Understanding: Not only extract text from images but also understand the context of the visual content. For example, if a user uploads an image of a teddy bear, AI will recognize it as such.
• 🔀 AI Image to Video: Turn images into dynamic videos with contextual understanding.
• 📸 AI Professional Headshots: Generate professional-quality avatars or profile photos with AI.
• ✂ AI Image Editor, Resizer and Compressor, Upscale: Enhance, optimize, and upscale your images with AI-powered tools.
• 🎼 AI Music to Music: Enhance or transform existing music tracks by inputting an audio file. AI analyzes your music and generates a continuation or variation, offering a new twist on your original piece.
• 🗣 AI Voice Chat: Experience interactive voice responses with AI personalities.
• ☁ Cloud Storage: All content generated is saved to the cloud, ensuring you can access your creations from any device, anytime.

Which Languages Does AI4Chat Support?

How do i toggle between different ai models, can i personalize my chats, what is a credit, can i upgrade, downgrade, or cancel my current plan anytime, what happens if i run out of credits, do unused credits carry forward to the next month, is there an option for unlimited usage, do i need a credit card to get started, what is the refund policy for subscriptions and one-time credit purchases, are payments safe, do you offer team or volume discounts, do you offer api access, can i use generated content for commercial purposes, is it easy to cancel my membership, where can i download the ai4chat mobile app, can i use the content generated using ai4chat for commercial purposes, how do i contact support, more questions, all set to level up your content game.

All in One AI platform for AI chat, image, video, music, and voice generatation. Create custom AI bots and workflows in minutes from any device, anywhere.

• AI Art & Images
• AI Music & Voice

AI4Chat © 2024. All Rights Reserved.

• Privacy Policy

Use Our Free A/B Testing Hypothesis Generator . Never Miss Key Elements From Your Hypotheses. Get Big Conversion Lifts.

Observation, inadvertent impact.

Streamline Your Hypothesis Generation Research with Custom Templates the Pros Use.

Have questions about a/b testing hypotheses, what is a hypothesis.

Many people define a hypothesis as an “educated guess”.

To be more precise, a properly constructed hypothesis predicts a possible outcome to an experiment or a test where one variable (the independent one ) is tweaked and/or modified and the impact is measured by the change in behavior of another variable (generally the dependent one).

A hypothesis should be specific (it should clearly define what is being altered and what is the expected impact), data-driven (the changes being made to the independent variable should be based on historic data or theories that have been proven in the past), and testable (it should be possible to conduct the proposed test in a controlled environment to establish the relationship between the variables involved, and disprove the hypothesis - should it be untrue.)

What is the Cost of a Hastily Assembled Hypothesis?

According to an analysis of over 28,000 tests run using the Convert Experiences platform, only 1 in 5 tests proves to be statistically significant.

While more and more debate is opening up around sticking to the concept of 95% statistical significance, it is still a valid rule of thumb for optimizers who do not want to get into the fray with peeking vs. no peeking, and custom stopping rules for experiments.

There might be a multitude of reasons why a test does not reach statistical significance. But framing a tenable hypothesis that already proves itself logistically feasible on paper is a better starting point than a hastily assembled assumption.

Moreover, the aim of an A/B test may be to extract a learning, but some learnings come with heavy costs. 26% decrease in conversion rates to be specific.

A robust hypothesis may not be the answer to all testing woes, but it does help prioritisation of possible solutions and leads testing teams to pick low hanging fruits.

How is an A/B Testing Hypothesis Different?

An A/B test should be treated with the same rigour as tests conducted in laboratories. That is an easy way to guarantee better hypotheses, more relevant experiments, and ultimately more profitable optimization programs.

The focus of an A/B test should be on first extracting a learning , and then monetizing it in the form of increased registration completions, better cart conversions and more revenue.

If that is true, then an A/B test hypothesis is not very different from a regular scientific hypothesis. With a couple of interesting points to note:

• Most scientific hypotheses proceed with one independent variable and one dependent variable, for the sake of simplicity. But in A/B tests, there might be changes made to several independent variables at the same time. Under such circumstances it is good to explore the relationship between the independent variables to make sure that they do not inadvertently impact one another. For example changing both the value proposition and button copy of a landing page to determine improvement in click through or completion rates is tricky. Reaching a point where the browser is compelled to click the button could easily have been impacted by the value proposition (as in a strong hook and heading). So what caused the improvement in the dependent variable? Was it the change to the first element or the second one?
• The concept of Operational Definition is non-negotiable in most laboratory experiments. And comes baked with the question of ethics or morality. Operation Definition is the specific process that will be used to quantify the change in the value/behavior of the independent variable in the test. As an example, if a test wishes to measure the level of frustration that subjects experience when they are exposed to certain stimuli, researchers must be careful to define exactly how they will measure the output or frustration. Should they allow the test subjects to act out, in which case they may hurt or harm other individuals. Or should they use a non-invasive technique like an fMRI scan to monitor brain activity and collect the needed data. In A/B tests however, since data is collected through relatively inanimate channels like analytics dashboards, generally little thought is spared to Operational Definition and the impact of A/B testing on the human subjects (site traffic in this case).

The 5 Essential Parts of an A/B Testing Hypothesis

A robust A/B testing hypothesis should be assembled in 5 key parts:

1. OBSERVATION

This includes a clear outline of the problem (the unexplained phenomenon) observed and what it entails. This section should be completely free of conjecture and rely solely on good quality data - either qualitative and/or quantitative - to bring a potential area of improvement to light. It also includes a mention of the way in which the data is collected.

Proper observation ensures a credible hypothesis that is easy to “defend” later down the line.

2. EXECUTION

This is the where, what, and the who of the A/B test. It specifies the change(s) you will be making to site element(s) in an attempt to solve the problem that has been outlined under “OBSERVATION”. It serves to also clearly define the segment of site traffic that will be exposed to the experiment.

Proper execution guidelines set the rhythm for the A/B test. They define how easy or difficult it will be to deploy the test and thus aid hypothesis prioritization .

This is where you make your educated guess or informed prediction. Based on a diligently identified OBSERVATION and EXECUTION guidelines that are possible to deploy, your OUTCOME should clearly mention two things:

• The change (increase or decrease) you expect to see to the problem or the symptoms of the problem identified under OBSERVATION.
• The Key Performance Indicators (KPIs) you will be monitoring to gauge whether your prediction has panned out, or not.

In general most A/B tests have one primary KPI and a couple of secondary KPIs or ways to measure impact. This is to ensure that external influences do not skew A/B test results and even if the primary KPI is compromised in some way, the secondary KPIs do a good job of indicating that the change is indeed due to the implementation of the EXECUTION guidelines, and not the result of unmonitored external factors.

4. LOGISTICS

An important part of hypothesis formulation, LOGISTICS talk about what it will take to collect enough clean data from which a reliable conclusion can be drawn. How many unique tested visitors, what is the statistical significance desired, how many conversions is enough and what is the duration for which the A/B test should run? Each question on its own merits a blog or a lesson. But for the sake of convenience, Convert has created a Free Sample Size & A/B/N Test Duration Calculator .

Set the right logistical expectations so that you can prioritise your hypotheses for maximum impact and minimum effort .

5. INADVERTENT IMPACT

This is a nod in the direction of ethics in A/B testing and marketing, because experiments involve humans and optimizers should be aware of the possible impact on their behavior.

Often a thorough analysis at this stage can modify the way impact is measured or an experiment is conducted. Or Convert certainly hopes that this will be the case in future. Here’s why ethics do matter in testing.

Now Organize, Prioritise & Learn from Your Hypotheses.

Try convert experiences in free trial & access convert compass beta - our hypothesis management platform., always working to improve outcomes..

Start Your 15 -Day Free Trial Right Now. No Credit Card Required

Important. Please Read.

• Check your inbox for the password to Convert’s trial account.
• Log in using the link provided in that email.

This sign up flow is built for maximum security. You’re worth it!

Collaborate with anyone, anywhere .

Use Hypothesis to annotate anything online with classmates, colleagues, or friends. Create a free personal account , or talk to our sales team about Education solutions.

Get Started

Bringing content and conversation together.

Hypothesis adds a collaborative layer over any online content. Through the power of social annotation, we can make online discussions more meaningful, productive, and engaging.

Hypothesis is for

Keep students engaged and connected with a seamless learning experience.

Create a new method of peer review and engagement for researchers and publications.

Share and discuss intriguing content with family, friends, and like-minded groups.

Comment on and highlight what interests you.

Annotate articles, websites, videos, documents, apps, and more – without clicking away or posting elsewhere. Hypothesis is easy to use and based on open web standards, so it works across the entire internet.

Turn annotations into conversations.

Classrooms, coworkers, and communities can share ideas, ask questions, and respond to annotations. Set groups to public or private to create your ideal discussion.

Build durable, shared knowledge.

No more losing valuable knowledge across email, forums, and apps.  Annotations are saved at the source and accessible to everyone, preserving commentary in context.

• 01. Comment & Highlight
• 02. Conversations
• 03. Knowledge

Changing online discussions for good.

Hypothesis is a mission-driven organization building universal collaboration into the internet with open-source technology.

Vision and Values

Start the conversation.

Create a free account and install the Hypothesis browser extension to start annotating. For Education  solutions, contact our sales team.

Create A Free Account Contact Sales Team

Online Hypothesis Generator

Add the required information into the fields below to build a list of well-formulated hypotheses.

• If patients follow medical prescriptions, then their condition will improve.
• If patients follow medical prescriptions, then their condition will show better results.
• If patients follow medical prescriptions, then their condition will show better results than those who do not follow medical prescriptions.
• H0 (null hypothesis) - Attending most lectures by first-year students has no effect on their exam scores.
• H1 (alternative hypothesis) - Attending most lectures by first-year students has a positive effect on their exam scores.

* Hint - choose either null or alternative hypothesis

⭐️ Hypothesis Creator: the Benefits

• 🔎 How to Use the Tool?
• 🤔 What Is a Hypothesis?
• 👣 Steps to Generating a Hypothesis
• 🔍 References

🔎 Hypothesis Generator: How to Use It?

The generation of a workable hypothesis is not an easy task for many students. You need to research widely, understand the gaps in your study area, and comprehend the method of hypothesis formulation to the dot. Lucky for you, we have a handy hypothesis generator that takes hours of tedious work out of your study process.

To use our hypothesis generator, you’ll need to do the following:

• Indicate your experimental group (people, phenomena, event)
• Stipulate what it does
• Add the effect that the subject’s activities produce
• Specify the comparison group

Once you put all this data into our online hypothesis generator, click on the “Generate hypothesis” tab and enjoy instant results. The tool will come up with a well-formulated hypothesis in seconds.

🤔 What Is a Research Hypothesis?

A hypothesis is a claim or statement you make about the assumed relationship between the dependent and independent variables you're planning to test. It is formulated at the beginning of your study to show the direction you will take in the analysis of your subject of interest.

The hypothesis works in tandem with your research purpose and research question , delineating your entire perspective.

For example, if you focus on the quality of palliative care in the USA , your perspective may be as follows.

This way, your hypothesis serves as a tentative answer to your research question, which you aim to prove or disprove with scientific data, statistics, and analysis.

Hypothesis Types

In most scholarly studies, you’ll be required to write hypotheses in pairs – as a null and alternative hypothesis :

• The alternative hypothesis assumes a statistically significant relationship between the identified variables. Thus, if you find that relationship in the analysis process, you can consider the alternative hypothesis proven.
• A null hypothesis is the opposite; it assumes that there is no relationship between the variables. Thus, if you find no statistically significant association, the null hypothesis is considered proven.

A handy example is as follows:

You are researching the impact of sugar intake on child obesity. So, based on your data, you can either find that the number of sugar spoons a day directly impacts obesity or that the sugar intake is not associated with obesity in your sample. The hypotheses for this study would be as follows:

ALTERNATIVE

There is a relationship between the number of sugar spoons consumed daily and obesity in U.S. preschoolers.

There is no relationship between the number of sugar spoons consumed daily and obesity in U.S. preschoolers.

Besides, hypotheses can be directional and non-directional by type:

• A directional hypothesis assumes a cause-and-effect relationship between variables, clearly designating the assumed difference in study groups or parameters.
• A non-directional hypothesis , in turn, only assumes a relationship or difference without a clear estimate of its direction.

NON-DIRECTIONAL

Students in high school and college perform differently on critical thinking tests.

DIRECTIONAL

College students perform better on critical thinking tests that high-school students.

👣 How to Make a Hypothesis in Research

Now let’s cover the algorithm of hypothesis generation to make this process simple and manageable for you.

Step #1: Formulate Your Research Question

The first step is to create a research question . Study the topic of interest and clarify what aspect you're fascinated about, wishing to learn more about the hidden connections, effects, and relationships.

Step #2: Research the Topic

Next, you should conduct some research to test your assumption and see whether there’s enough published evidence to back up your point. You should find credible sources that discuss the concepts you’ve singled out for the study and delineate a relationship between them. Once you identify a reasonable body of research, it’s time to go on.

Step #3: Make an Assumption

With some scholarly data, you should now be better positioned to make a researchable assumption.

For instance, if you find out that many scholars associate heavy social media use with a feeling of loneliness, you can hypothesize that the hours spent on social networks will directly correlate with perceived loneliness intensity.

Step #4: Improve Your Hypothesis

Now that you have a hypothesis, it’s time to refine it by adding context and population specifics. Who will you study? What social network will you focus on? In this example, you can focus on the student sample’s use of Instagram .

Step #5: Try Different Phrasing

The final step is the proper presentation of your hypothesis. You can try several variants, focusing on the variables, correlations , or groups you compare.

For instance, you can say that students spending 3+ hours on Instagram every day are lonelier than their peers. Otherwise, you can hypothesize that heavy social media use leads to elevated feelings of loneliness.

👀 Null Hypothesis Examples

If you’re unsure about how to generate great hypotheses, get some inspiration from the list of examples formulated by our writing pros.

Thank you for reading this article! If you’re planning to analyze business issues, try our free templates: PEST , PESTEL , SWOT , SOAR , VRIO , and Five Forces .

❓ Hypothesis Generator FAQ

❓ what does hypothesis mean.

A hypothesis in an essay or a larger research assignment is your claim or prediction of the relationship you assume between the identified dependent and independent variables. You share an assumption that you’re going to test with research and data analysis in the later sections of your paper.

❓ How to create a hypothesis?

The first step to formulating a good hypothesis is to ask a question about your subject of interest and understand what effects it may experience from external sources or how it changes over time. You can identify differences between groups and inquire into the nature of those distinctions. In any way, you need to voice some assumption that you’ll further test with data; that assumption will be your hypothesis for a study.

❓ What is a null and alternative hypothesis?

You need to formulate a null and alternative hypothesis if you plan to test some relationship between variables with statistical instruments. For example, you might compare a group of students on an emotional intelligence scale to determine whether first-year students are less emotionally competent than graduates. In this case, your alternative hypothesis would state that they are, and a null hypothesis would say that there is no difference between student groups.

❓ What does it mean to reject the null hypothesis?

A null hypothesis assumes that there is no difference between groups or that the dependent variables don't have any sizable impact on the independent variable. If your null hypothesis gets rejected, it means that your alternative hypothesis has been proved, showing that there is a tangible difference or relationship between your variables.

🔗 References

• How to Write a Hypothesis in 6 Steps - Grammarly
• The Hypothesis in Science Writing
• Hypothesis Definition & Examples - Simply Psychology
• Hypothesis Examples: Different Types in Science and Research
• Forming a Good Hypothesis for Scientific Research

Free Essay Hypothesis Generator

Writing an essay hypothesis might be challenging: it has to be well-structured and follow specific standards. But we have a solution! Our free essay hypothesis generator is here to help you. Check it out and take your writing to the next level!

• If high school students receive sex education, then their ability to prevent unwanted pregnancy will improve as compared to those who do not receive sex education.
• If high school students receive sex education, then their ability to prevent unwanted pregnancy will show better results than those who do not receive sex education.
• H0 (null hypothesis) - If high school students receive sex education, it has no effect on their ability to prevent unwanted pregnancy as compared to those who do not receive sex education.
• H1 (alternative hypothesis) - If high school students receive sex education, it has a negative effect on their ability to prevent unwanted pregnancy as compared to those who do not receive sex education.
• If high school students receive sex education, then their ability to prevent unwanted pregnancy will worsen as compared to those who do not receive sex education.
• If high school students receive sex education, then their ability to prevent unwanted pregnancy will show worse results than those who do not receive sex education.
• H1 (alternative hypothesis) - If high school students receive sex education, it has a positive effect on their ability to prevent unwanted pregnancy as compared to those who do not receive sex education.
• ✅ Why Use Our Generator?
• 🤔 What Is an Essay Hypothesis?
• ✍️ How to Write a Hypothesis?
• ✨ Hypothesis Examples

👌 Hypothesis Maker: the Benefits

🔗 references, ✅ why use our essay hypothesis generator.

We are sure you will enjoy using Overnight Essay's essay hypothesis generator. Check out its awesome benefits:

🤔 Null and Alternative Hypothesis

An essay hypothesis is a claim that predicts the outcome of your research and tests the relationship between two variabilities . Your research can either prove or disprove it.

Like a thesis statement, an essay hypothesis is an answer to your research question. However, there is a difference:

• A hypothesis shows your ability to make a logical assumption. It can be supported by observations, statistical analysis, experiments, or other scientific research methods. It's usually used for quantitative analysis .
• A thesis statement defines your research and sums up its main points. We can use it for both quantitative and qualitative analysis. A thesis can be formulated manually or generated automatically .

Components of a Hypothesis

To write a solid hypothesis, you should define your variables first. There are two types of them: independent and dependent :

• An independent variable can be controlled by a researcher during an experiment.
• A dependent variable can only be measured and observed.

Let’s take a closer look.

Suppose your research is about the effect of having pets on mental well-being. Your hypothesis might be:

Spending more time playing with your pet positively affects one's mental health.

Here, the amount of time spent playing with a pet is an independent variable because this is something we can change and control. Therefore, the positive effect is the dependable variable since we can only observe it.

Types of Hypotheses

A hypothesis may vary depending on the goal and nature of your research. So, let’s break down several types of them.

• A statistical hypothesis tests a limited sample of a population . It uses statistics to calculate the result.
• A simple hypothesis tests a relationship between two variables and predicts the potential result of the research.
• An empirical or working hypothesis is based on factual data. It is used to create a theory for testing .
• A complex hypothesis tests a relationship between two or more dependent or independent variables.
• A logical hypothesis predicts the result of your research with no evidence or actual data but based on deduction.
• A null hypothesis is created to show that there is no relationship between variables. It is abbreviated as H0.
• An alternative hypothesis disproves a null hypothesis and states the opposite. It is abbreviated as H1 or HA.

✍️ How to Make a Hypothesis for an Essay

So, now you know what a hypothesis is. But how exactly do you write it? Here’s a step-by-step process.

Knowing the hypothesis will help you create an outline and topic sentences for your paper.

✨ Good Essay Hypothesis Examples

To understand what an essay hypothesis should be like, check out the examples below and see what makes them good.

We hope this article was helpful for you. Check out our essay hypothesis generator, topic generator , sentence rephraser , and other tools. Good luck with your studies!

❓ Hypothesis Maker FAQ

📍 how do you write a hypothesis for an essay, 📍 what is an example of a hypothesis, 📍 what are the 3 types of hypotheses.

• A simple hypothesis introduces a relationship between an independent and dependent variable.
• A complex one includes the relationship between two or more variables.
• Finally, a directional hypothesis includes the direction of the expected result.

📍 How to introduce a hypothesis in an essay?

• How to Write a Hypothesis: Grammarly
• Research Hypothesis: Oakland University
• How to Write a Hypothesis to an Analytical Essay: Classroom
• What Is the Difference Between a Thesis Statement and a Hypothesis Statement?: American Public University System

Hypothesis Builder

Formulating a strong hypothesis is the foundation of a successful split test. A good hypothesis has three main components:

• Comprehension – Identifying something that can be improved upon
• Response – Change that can cause improvement
• Outcome – Measurable result of change that determines success

Don’t know where to start? We’ve got you covered. Use this hypothesis builder to assemble all the information you need.

We have observed by .

We want to at on for .

This should lead to , which will be measured by and backed up by .

Need Help Testing Your New Hypothesis?

Thanks to the builder above you’ve got a great hypothesis on your hands, but now what? How does that translate into a test? What tools should I use? Which test should I run first?

You have questions. We have answers. We can help.

from assumptions to testable hypotheses.

You'll start asking the question what impact you can make in which way and for who..

What is it for?

Convert your riskiest assumptions into testable hypotheses.

• Formulate your hypothesis in a waterproof way
• Hypothesis structure: if we do X, then Y% of the target audience will behave in way Z.

Step by step guide

Download the pdf.

Pick your riskiest assumption.

Define the X-variable. What action are you going to take to test this assumption. Write down your specific repeatable action.

Define the Y-variable. Make sure you vanity check your metric. Be as specific as possible when it comes to your target audience.

Define the Z-variable. What action does your target audience have to take in order for this experiment to be a success? What is the expected measurable action?

Write down your leading indicators. What are the metrics you can track that represent necessary actions to achieve your success goal?

Get the tool

Download our H ypothesis C reator and convert your riskiest assumptions into testable hypotheses.

Related tools

Do you need more we have many tools, official press release: ants connect acquires cosmos collective.

By continuing to browse this website, you agree to our use of cookies

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base

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

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

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

There are 5 main steps in hypothesis testing:

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

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

Table of contents

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

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

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

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

Prevent plagiarism. Run a free check.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Methodology

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

Research bias

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

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

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

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

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

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

Bevans, R. (2023, June 22). Hypothesis Testing | A Step-by-Step Guide with Easy Examples. Scribbr. Retrieved September 9, 2024, from https://www.scribbr.com/statistics/hypothesis-testing/

Is this article helpful?

Rebecca Bevans

Other students also liked, choosing the right statistical test | types & examples, understanding p values | definition and examples, what is your plagiarism score.

Hypothesis Generator

Generate hypotheses for your research.

• Academic Research: Generate hypotheses for your thesis, dissertation, or any academic paper.
• Data Analysis: Create hypotheses to guide your data exploration and analysis.
• Market Research: Develop hypotheses to understand market trends and consumer behavior.
• Product Development: Formulate hypotheses to guide your product testing and development process.
• Scientific Research: Generate hypotheses for your experiments or observational studies.

New & Trending Tools

Get webpage text from url, ai web scraper, ai resume updater.

World-Class

Data Science

Learn with instructors from:

History Hypothesis Generator

If you’re searching for a hypothesis generator, you’re in the right place! With this free online tool, you’ll easily make a hypothesis from a question or from scratch.

Need a hypothesis for your history paper? This automatic hypothesis generator will save your time and nerves! Follow these 3 steps:

• ❓ Definitions
• 💡 What’s This Tool?

🔬 How to Generate a Hypothesis from a Question?

• ✅ Characteristics
• ✍️ Examples

🔗 References

❓ hypothesis in history: definitions.

In high school or college, you might need to develop a historical hypothesis for your academic paper or any other project. In the sections below, we have explained what it means for this subject.

What Is a Hypothesis?

A hypothesis is a statement or proposed explanation for a phenomenon. For it to be scientific, researchers should be able to test it.

The words “hypothesis” and “ theory ” are often used interchangeably. However, they are not the same. In exact science, a hypothesis needs to be provable to become a theory. In the non-scientific environment, the word is used more loosely.

What about a Hypothesis in History?

A historical hypothesis consists of:

• Attitudes that demonstrate relations between variables.

It is a proposed explanation for a phenomenon different from recorded facts , which is useful when:

• the existing evidence is limited,
• no recognized historical methodology is available,
• or researchers want to examine a specific aspect of a historical event.

A reasonable hypothesis should give a straightforward answer with substantial explanatory power . If you also need a unique idea to write about, check our list of history topics.

Hypothesis vs. Theory

💡 Hypothesis Maker: What It Is

An automatic hypothesis generator is a tool that can save you time and energy. It uses advanced AI technology to create an appropriate assumption:

• The generator analyzes the variables you have input into the cycle.
• Then, it formulates the relations between them.
• Finally, it generates a hypothesis that you can use for your paper.

Our history hypothesis generator is a straightforward tool. You can use it whenever you need help inventing or wording your idea. It’s free and available all the time!

At a particular stage of your research, you will need to generate a hypothesis from a research question. A hypothesis is a statement that you will further test.

To do that, you need to take five steps:

• Define independent and dependent variables.
• Brainstorm ideas to explain the question.
• Choose the most convincing explanation.
• Formulate a statement based on this explanation.
• Check if the claim is testable in a scientific study.

✅ How to Make a Good Hypothesis in History

So that you don’t get confused when developing your historical hypothesis, let’s see what characteristics a successful one should obtain:

✍️ History Hypothesis Maker: Examples

So, you’ve read about the characteristics of a good hypothesis in history. Now you may be wondering what one actually looks like. In this section, we have listed some examples based on sample academic papers .

Italian industrial capacities were underutilized, while other Axis partners exploited their capabilities. Such countries as Hungary, Bulgaria, and Slovakia even granted loans to Nazi Germany. The WWII could have ended differently if German-Italian cooperation had been more efficient.

People from dominant racial groups deny racism because they are ignorant of human history. At the same time, minorities see the issue differently. They are aware of the records and experience systemic racism in the present.

Islamic Art has features distinctive from the Platonic influence on Islamic thought. Thus, there is a philosophical explanation of why it follows the principles of order and harmony.

The world ignored the Korean crisis in 1948 due to the situation in Germany and the deterioration of Soviet-American relations.

Thanks for reading!

If you’re working on a history paper, try out our automatic hypothesis generator. It will come up with great ideas and save you a lot of time. Use our tips and examples to make your paper and research better. Besides, share it with other students who may need our advice.

Updated: May 24th, 2024

• Hypothesis-Based Research | Michigan Tech
• A Brief Guide to Writing a History Paper | Harvard College
• Hypothesis Formulation | Boston University
• Developing a Hypothesis | Pressbooks

Hurricane Francine live updates: Louisiana hours away from landfall

Francine is forecast to make landfall as a Category 1 storm.

Hurricane Francine, now a Category 1 storm, is forecast to make landfall Wednesday afternoon or early evening in Louisiana, southwest of New Orleans.

Latest headlines:

• 45 minutes ago Latest forecast
• 9 hours and 5 minutes ago Conditions deteriorating in southern Louisiana
• 9 hours and 24 minutes ago 'The time to evacuate has now passed'
• 10 hours and 35 minutes ago New Orleans residents should start sheltering in place

Latest forecast

Tropical storm conditions have reached the Louisiana coastline, and life-threatening storm surge and hurricane-force winds are expected to begin in the next few hours leading up to Hurricane Francine’s landfall.

A hurricane watch is in effect in New Orleans, where the worst impacts will be Wednesday afternoon through Wednesday night.

A tornado watch has been issued for parts of Mississippi and Louisiana, including New Orleans.

Storm surge will worsen throughout the day. Up to 10 feet of storm surge is possible in parts of Louisiana; up to 5 feet is possible in the New Orleans area.

Flash flooding is a major threat for Louisiana and Mississippi.

Conditions across Louisiana will start to improve overnight as Francine weakens and moves north into Mississippi.

Francine will rapidly weaken after landfall and become a tropical storm by Thursday, but it’ll still bring heavy rain to the South.

Flash flooding will remain a threat through the end of the week as Francine moves north into Tennessee, Kentucky and Missouri.

The threat for isolated tornadoes will continue through Thursday morning, especially in Alabama and the Florida Panhandle.

-ABC News’ Melissa Griffin

Conditions deteriorating in southern Louisiana

Conditions are deteriorating in southern Louisiana as Hurricane Francine gets closer to landfall.

The storm, located 120 miles southwest of Morgan City, Louisiana, is moving northeast at 13 mph.

Rain bands are moving on shore and the dangerous winds are closing in.

'The time to evacuate has now passed'

With hours to go until Hurricane Francine makes landfall in Louisiana, "the time to evacuate has now passed," Jacques Thibodeau, the director of the Governor's Office of Homeland Security and Emergency Preparedness, said at a news conference.

"It is now time to go down and hunker down," he said. "We are no longer in the, 'Prepare for a hurricane' -- we are now in the, 'Respond to a hurricane.'"

The White House has approved an emergency declaration for the state. The Louisiana National Guard expects to have 2,400 guardsmen ready for the storm, along with 58 boats, 101 high water vehicles and 61 aircrafts, officials said.

Louisiana Gov. Jeff Landry said he’s been in contact with the Federal Emergency Management Agency and the Army Corps of Engineers, and said he’s fully confident in all state and federal agencies working together before, during and after the hurricane.

Landry also encouraged residents to “take advantage of the power that you have currently and make sure that you charge all of your devices.”

-ABC News’ Alexandra Faul

New Orleans residents should start sheltering in place

Residents in New Orleans should stay off the roads beginning at noon ET and remain sheltered in place until Thursday morning, Mayor LaToya Cantrell said.

"Conditions will worsen throughout the day—stay safe!" she tweeted.

Top Stories

Fact-checking Kamala Harris and Donald Trump's 1st presidential debate

• Sep 11, 7:08 AM

READ: Harris-Trump presidential debate transcript

• Sep 10, 11:58 PM

All-hands-on-deck ordered as 3 LA-area wildfires have burned more than 100,000 acres

Watch the full ABC News presidential debate

• Sep 11, 7:55 AM

Trump-Harris debate updates: Candidates go on attack in zinger-filled showdown

• Sep 11, 12:52 AM