writing a hypothesis using if and then

Hypothesis If Then

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In the vast universe of scientific inquiries, the “if-then” hypothesis structure stands out as an essential tool, bridging observation and prediction. This format not only simplifies complex scientific theories but also provides clarity to young learners and budding scientists. Whether you’re experimenting in a professional lab or just in your backyard, understanding and crafting a Thesis statement succinct “if-then” hypothesis can be the key to unlocking the secrets of the world around us. Dive in to explore, write, and refine!

What is If Then Hypothesis?

The “If-Then” hypothesis is a predictive statement that sets up a cause-and-effect relationship between two variables. It’s structured such that the “If” portion introduces a condition or a cause, and the “Then” portion predicts the effect or outcome of that condition. This format helps in clearly establishing a link between the independent and dependent variables in an experiment.

What is an example of a Hypothesis If Then Statement?

For instance, let’s consider a basic experiment related to plant growth:

Hypothesis : If a plant is exposed to direct sunlight for at least 6 hours a day, then it will grow taller than a plant that is kept in the shade.

In this example, the exposure to sunlight (or the lack thereof) is the condition, while the growth of the plant is the predicted outcome. The statement concisely links the cause (sunlight exposure) to the effect (plant growth).

100 If Then Hypothesis Statement Examples

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The “If-Then” hypothesis elegantly captures a cause-and-effect relationship in scientific inquiries. This predictive format, with its concise clarity, bridges observation and anticipated outcome, guiding experiments in a myriad of domains.

Plant Growth : If a plant receives fertilizer, then it will grow faster than one without fertilizer.
Melting Points : If ice is exposed to temperatures above 0°C, then it will melt.
Battery Life : If a battery is used continuously, then it will drain faster than if used intermittently.
Sleep & Performance : If a person sleeps less than 6 hours a night, then their cognitive performance will decrease.
Diet & Weight : If an individual consumes more calories than they burn, then they will gain weight.
Hydration : If a person drinks less than 8 glasses of water daily, then they may experience dehydration.
Light & Vision : If a room is darkened, then the pupils of one’s eyes will dilate.
Sugar & Energy : If children consume sugary drinks, then they will show increased levels of energy.
Study Habits : If a student revises regularly, then they will retain more information than those who cram.
Exercise & Health : If a person exercises three times a week, then their cardiovascular health will improve.
Noise & Concentration : If a room is noisy, then people inside will find it harder to concentrate.
Medication & Pain : If an individual takes painkillers, then they will report reduced pain levels.
Soil Quality : If soil is rich in nutrients, then plants grown in it will be healthier.
Reading & Vocabulary : If a child reads daily, then their vocabulary will expand faster than a non-reading peer.
Social Media : If a teenager spends over 5 hours on social media, then they may experience decreased sleep quality.
Sunscreen : If sunscreen is applied, then the chances of getting sunburned decrease.
Coffee & Alertness : If an individual drinks coffee in the morning, then they will feel more alert.
Music & Productivity : If calming music is played in the workplace, then employees will be more productive.
Temperature & Metabolism : If the ambient temperature is cold, then a person’s metabolism will increase.
Pets & Stress : If an individual owns a pet, then their stress levels might decrease.
Vegetation & Air Quality : If trees are planted in an urban area, then air quality will improve.
Vaccination : If a child is vaccinated, then they will have a reduced risk of contracting certain diseases.
E-learning : If students use e-learning platforms, then they will have flexible study hours.
Recycling : If a community adopts recycling, then landfill waste will decrease.
Fast Food : If an individual eats fast food regularly, then their cholesterol levels might rise.
UV Light : If UV light is shone on a glow-in-the-dark material, then it will glow more brightly.
Brushing Teeth : If a child brushes their teeth twice daily, then they will have fewer cavities than those who don’t.
Bird Migration : If the climate becomes colder, then certain birds will migrate to warmer regions.
Space Exploration : If astronauts go without gravity for long periods, then their bone density will decrease.
Plastic Pollution : If we reduce single-use plastic consumption, then the amount of plastic in the ocean will decrease.
Books & Imagination : If a child reads fantasy novels, then their imaginative skills will be enhanced.
AI & Efficiency : If companies use artificial intelligence in operations, then their efficiency will improve.
Video Games : If children play violent video games, then they might exhibit aggressive behavior.
Healthy Diet : If someone consumes a balanced diet, then their overall health will benefit.
Deforestation : If forests are cleared at the current rate, then global temperatures will rise due to reduced carbon sequestration.
Renewable Energy : If a country invests in renewable energy, then its carbon footprint will decrease.
Exercise & Mood : If an individual engages in regular physical activity, then their mood will generally improve.
Microplastics : If microplastics enter the water system, then marine life will be at risk.
Language Learning : If a person practices a new language daily, then they will become fluent faster.
Organic Farming : If farmers use organic methods, then the pesticide residue in the food will decrease.
Remote Work : If employees work remotely, then office costs will reduce.
Yoga & Flexibility : If someone practices yoga regularly, then their flexibility will increase.
Public Transport : If a city improves its public transportation system, then traffic congestion will decrease.
Meditation & Stress : If an individual meditates daily, then their stress levels will be lower.
Fish & Omega-3 : If someone includes fish in their diet weekly, then their omega-3 fatty acid intake will be adequate.
Smartphones & Sleep : If a person uses their smartphone before bed, then their sleep quality might decrease.
Waste Segregation : If households segregate waste, then recycling processes will be more efficient.
E-Books : If students use e-books instead of paper ones, then paper consumption will decrease.
Carpooling : If more people adopt carpooling, then urban air quality will improve due to fewer car emissions.
Digital Payments : If digital payment systems are adopted widely, then cash handling costs will reduce.
Online Learning : If students engage in online learning platforms, then their access to diverse educational resources will increase.
Tree Planting : If a community plants more trees in urban areas, then the air quality will improve due to increased oxygen output.
Pet Ownership : If an individual adopts a pet, then they may experience reduced feelings of loneliness.
Recycling : If recycling is made mandatory in cities, then landfill waste will decrease significantly.
Natural Cleaners : If households use natural cleaning agents, then water pollution from residential areas will decrease.
Solar Panels : If a house installs solar panels, then its electricity bill will decrease.
Music & Productivity : If workers listen to instrumental music while working, then their productivity might increase.
Healthy Breakfast : If someone eats a nutritious breakfast daily, then their energy levels throughout the day will be higher.
Water Conservation : If individuals reduce their shower time by 5 minutes, then significant water conservation can be achieved annually.
Learning Instruments : If a child learns a musical instrument, then their cognitive and motor skills may improve.
Reusable Bags : If shoppers use reusable bags, then the demand for plastic bags will reduce.
Public Libraries : If a city invests in public libraries, then the literacy rate of its citizens may rise.
Organ Donation : If awareness about organ donation increases, then the waiting list for organ transplants will decrease.
Green Spaces : If urban areas increase green spaces, then residents’ mental well-being may improve.
Sleep & Memory : If a student gets at least 8 hours of sleep, then their memory retention might be better.
Digital Detox : If someone takes a weekly digital detox day, then their stress levels may decrease.
Composting : If households start composting kitchen waste, then the amount of organic waste in landfills will reduce.
Gardening & Health : If individuals engage in gardening activities, then they might experience improved mental health.
Flu Vaccination : If a person gets a flu shot annually, then their chances of getting influenza will reduce.
Hand Washing : If people wash their hands regularly, then the spread of common diseases may decrease.
Diverse Diet : If someone consumes a diverse range of vegetables, then they will have a better nutrient intake.
Physical Books : If a student reads from physical books instead of screens, then they might have better sleep patterns.
Mindfulness & Anxiety : If an individual practices mindfulness exercises, then their anxiety levels may decrease.
Green Vehicles : If a city promotes the use of electric vehicles, then air pollution levels will reduce.
Walking & Health : If someone walks 10,000 steps daily, then their cardiovascular health might improve.
Art & Creativity : If children are exposed to art classes from a young age, then their creative thinking skills may enhance.
Dark Chocolate : If someone consumes dark chocolate regularly, then their antioxidant intake may increase.
Yoga & Flexibility : If an individual practices yoga thrice a week, then their flexibility and posture may improve.
Cooking at Home : If families cook meals at home more frequently, then their intake of processed foods might decrease.
Local Tourism : If local tourism is promoted, then a region’s economy can benefit due to increased business opportunities.
Reading Aloud : If parents read aloud to their children every night, then the children’s vocabulary and comprehension skills might expand.
Public Transportation : If cities improve their public transportation system, then the number of cars on the road might decrease.
Indoor Plants : If a person keeps indoor plants in their workspace, then their concentration and productivity may enhance due to better air quality.
Bird Watching : If an individual engages in bird watching, then their patience and observation skills might develop.
Biking to Work : If employees bike to work, then their cardiovascular health can improve and their carbon footprint might reduce.
Aquariums & Stress : If someone spends time watching fish in an aquarium, then their stress levels may decrease.
Meditation & Focus : If an individual meditates daily, then their attention span and focus might increase.
Learning Languages : If a student learns a new language, then their cognitive flexibility and memory retention may improve.
Community Gardens : If neighborhoods establish community gardens, then residents may benefit from fresh produce and community bonding.
Journaling : If someone journals their thoughts regularly, then their self-awareness and emotional processing might improve.
Volunteering : If an individual volunteers once a month, then their sense of purpose and community connection may strengthen.
Eco-friendly Products : If consumers prefer eco-friendly products, then industries might adopt more sustainable manufacturing practices.
Limiting Screen Time : If children limit their screen time to an hour a day, then their physical activity levels and sleep patterns may benefit.
Outdoor Play : If kids play outdoors regularly, then their motor skills and social interactions might develop better.
Therapy & Mental Health : If someone attends therapy sessions, then they may experience improved mental well-being and coping strategies.
Natural Light : If workspaces are designed to allow more natural light, then employee morale and productivity might rise.
Water Intake : If a person drinks at least 8 glasses of water daily, then their hydration levels and skin health may improve.
Classical Music : If students listen to classical music while studying, then their concentration might increase.
Home Composting : If households adopt composting, then garden soil quality might improve and organic waste in landfills may reduce.
Green Roofs : If buildings adopt green roofs, then urban heat islands might decrease, and biodiversity may benefit.

Hypothesis If Then Statement Examples in Research

The crux of experimental research revolves around predicting an outcome. An ‘If-Then’ hypothesis format succinctly conveys anticipated cause-and-effect relationships, enabling clearer comprehension and assessment.

DNA Sequencing : If we utilize CRISPR technology for DNA sequencing, then the accuracy of detecting genetic mutations may increase.
Drug Efficiency : If a new drug compound is introduced to malignant cells in vitro, then the proliferation rate of these cells might decrease.
Digital Learning : If students are exposed to AI-driven educational tools, then their academic performance might significantly improve.
Nano-technology : If nanoparticles are used in drug delivery, then the targeting of specific cells may become more efficient.
Quantum Computing : If quantum bits replace traditional bits in computing, then the processing speed might witness a revolutionary acceleration.

Hypothesis If Then Statement Examples about Climate Change

Understanding climate change necessitates predicting outcomes based on varied actions or occurrences. These hypotheses present potential scenarios in the vast realm of climate studies.

Deforestation : If deforestation rates continue at the current pace, then global carbon dioxide levels will rise significantly.
Solar Energy : If solar energy adoption increases by 50% in the next decade, then global reliance on fossil fuels might decrease considerably.
Ocean Temperatures : If the world’s oceans warm by another degree Celsius, then coral bleaching events may become twice as frequent.
Carbon Taxation : If a global carbon tax is implemented, then emissions from industries might see a drastic reduction.
Melting Ice Caps : If polar ice caps continue to melt at the current rate, then sea levels might rise to submerge several coastal cities by 2100.

Hypothesis If Then Statement Examples in Psychology

Psychology delves into understanding behaviors and mental processes. Formulating hypotheses in an ‘If-Then’ structure can streamline experimental setups and interpretations.

Mindfulness Meditation : If individuals practice daily mindfulness meditation, then symptoms of anxiety and stress may decrease.
Social Media : If teenagers spend over five hours daily on social media, then their self-esteem levels might drop.
Cognitive Behavioral Therapy : If patients with depression undergo cognitive-behavioral therapy, then their coping mechanisms may strengthen.
Sleep and Memory : If adults get less than six hours of sleep nightly, then their memory retention might deteriorate faster.
Nature Exposure : If urban residents are exposed to natural settings weekly, then their mental well-being might improve.

Alternative If Then Hypothesis Statement Examples

Sometimes, researchers propose alternate scenarios to challenge or complement existing beliefs. These hypotheses capture such alternative insights.

Vitamin Intake : If individuals consume Vitamin C supplements daily, then their immunity might not necessarily strengthen, contradicting popular belief.
Digital Detox : If tech professionals take a monthly digital detox day, then their productivity may not diminish, countering the notion that constant connectivity boosts efficiency.
Organic Foods : If consumers solely eat organic foods, then their overall health markers might remain unchanged, challenging the health superiority of organic diets.
Exercise Routines : If gym-goers switch to calisthenics from weight training, then muscle mass gain might remain consistent, offering an alternative to traditional gym workouts.
E-learning : If students transition from classroom learning to e-learning platforms, then their academic performance may not necessarily drop, challenging the indispensability of physical classrooms.

Hypothesis If Then Statement Examples in Biology

In biology, the interaction of living organisms and their environments often leads to distinct outcomes. The ‘If-Then’ hypothesis structure can efficiently predict these outcomes based on varying factors.

Cell Division : If a cell is exposed to radiation, then the rate of its division might decrease significantly.
Plant Growth : If plants are provided with blue light, then their growth rate might be faster compared to those exposed to red light.
Enzyme Activity : If the temperature of a reaction involving enzymes rises by 10°C, then the activity of the enzymes might double.
Animal Behavior : If nocturnal animals are exposed to continuous artificial light, then their feeding and reproductive behaviors might be disrupted.
Genetic Modification : If crops are genetically modified for drought resistance, then their yield in arid regions might increase substantially.

Hypothesis If Then Statement Examples in Chemistry

The realm of chemistry is filled with reactions and interactions. Predicting outcomes based on specific conditions is crucial, and the ‘If-Then’ hypothesis structure provides clarity in such predictions.

Acid-Base Reactions : If a solution has a pH below 7, then it might turn blue litmus paper red, indicating its acidic nature.
Temperature and Reaction Rate : If the temperature of a chemical reaction is increased, then the rate of that reaction might speed up.
Metal Reactivity : If zinc metal is placed in copper sulfate solution, then it might displace the copper, indicating its higher reactivity.
Organic Synthesis : If an alkene is treated with bromine water, then the solution might decolorize, suggesting the presence of a double bond.
Electrolysis : If an aqueous solution of sodium chloride undergoes electrolysis, then chlorine gas might be released at the anode.

Hypothesis If Then Statement Examples in Physics

Physics examines the fundamental principles governing our universe. ‘If-Then’ hypotheses help in determining cause-and-effect relationships amidst complex physical phenomena.

Gravity : If an object is dropped from a certain height in a vacuum, then it might accelerate at 9.81 m/s^2, irrespective of its mass.
Refraction : If light travels from air into water, then it might bend towards the normal due to the change in speed.
Magnetism : If a magnetic field is applied to a moving charged particle, then the particle might experience a force perpendicular to its direction of motion.
Thermal Expansion : If a metal rod is heated, then it might expand due to the increased kinetic energy of its atoms.
Quantum Mechanics : If an electron is observed in a quantum system, then its wave function might collapse, determining its position.

What is an if-then because hypothesis?

An “if-then-because” hypothesis is a structured statement that predicts the outcome of an experiment based on a proposed cause and effect scenario. The structure usually goes as follows: “If [I do this specific action], then [this particular result will occur] because [of this scientific reason].”

For example: “If I water plants with sugar water, then they will grow taller than the ones watered with plain water because sugar provides additional nutrients to the plants.”

This type of simple hypothesis statement not only predicts the outcome but also provides a reasoning for the expected outcome, thereby setting the groundwork for the experimental procedure and its subsequent analysis.

Is a hypothesis typically an if-then statement?

Yes, a hypothesis is often framed as an “if-then” statement, especially in experimental studies. This format succinctly presents a proposed cause and its expected effect. By specifying a relationship between two variables, it offers clarity to the hypothesis and makes the intended testing straightforward. However, while common, not all hypotheses are written in the “if-then” format.

Is an if-then statement a hypothesis or prediction?

An “if-then” statement can be both a hypothesis and a prediction. However, their contexts differ:

Hypothesis: It is a tentative explanation for an observation or phenomenon that can be tested experimentally. When written in the “if-then” format, it usually predicts a relationship between variables based on theoretical understanding.Example: “If a plant is given caffeine, then it will grow faster.”
Prediction: It is a specific, testable statement about what will happen under particular conditions. It is based on the hypothesis and narrows down the expected outcomes of an experiment.Example: “If a bean plant is watered with a 1% caffeine solution daily, then after one month, it will be 10% taller than plants watered with plain water.”

How do you write an If Then Hypothesis Statement? – A Step by Step Guide

Identify the Variables: Determine the independent variable (the factor you’ll change) and the dependent variable (the factor you’ll measure).
Frame the Relationship: Using your understanding of the topic, establish a potential relationship between the identified variables.
Start with “If”: Begin your hypothesis with “If” followed by your independent variable.
Follow with “Then”: After stating your independent variable, include “then” followed by the potential outcome or change in the dependent variable you expect.
Review for Clarity: Ensure your hypothesis is clear, concise, and testable. It should state a specific relationship between the variables.

Tips for Writing If Then Hypothesis

Be Specific: Ensure your variables are clearly defined. Instead of “If I water plants more,” use “If I water plants twice daily.”
Ensure Testability: Your hypothesis should propose a relationship that can be tested through an experiment.
Avoid Conclusions: A hypothesis is a prediction, not a conclusion. It shouldn’t state a known fact but should be based on prior knowledge.
Use Simple Language: Especially when the audience might not have a deep understanding of the topic. Keeping it straightforward ensures comprehension.
Revise and Refine: After drafting your hypothesis, revisit it to check for clarity, specificity, and relevance to the research question at hand.

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

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

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

How to Craft a Research Hypothesis

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

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

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

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

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

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

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

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

What are the Features of an Effective Hypothesis?

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

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

Understanding Null and Alternative Hypotheses in Research

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

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

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

Null Hypothesis:

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

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

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

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

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

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

References

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

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Hypothesis Examples

A hypothesis is a prediction of the outcome of a test. It forms the basis for designing an experiment in the scientific method . A good hypothesis is testable, meaning it makes a prediction you can check with observation or experimentation. Here are different hypothesis examples.

Null Hypothesis Examples

The null hypothesis (H 0 ) is also known as the zero-difference or no-difference hypothesis. It predicts that changing one variable ( independent variable ) will have no effect on the variable being measured ( dependent variable ). Here are null hypothesis examples:

Plant growth is unaffected by temperature.
If you increase temperature, then solubility of salt will increase.
Incidence of skin cancer is unrelated to ultraviolet light exposure.
All brands of light bulb last equally long.
Cats have no preference for the color of cat food.
All daisies have the same number of petals.

Sometimes the null hypothesis shows there is a suspected correlation between two variables. For example, if you think plant growth is affected by temperature, you state the null hypothesis: “Plant growth is not affected by temperature.” Why do you do this, rather than say “If you change temperature, plant growth will be affected”? The answer is because it’s easier applying a statistical test that shows, with a high level of confidence, a null hypothesis is correct or incorrect.

Research Hypothesis Examples

A research hypothesis (H 1 ) is a type of hypothesis used to design an experiment. This type of hypothesis is often written as an if-then statement because it’s easy identifying the independent and dependent variables and seeing how one affects the other. If-then statements explore cause and effect. In other cases, the hypothesis shows a correlation between two variables. Here are some research hypothesis examples:

If you leave the lights on, then it takes longer for people to fall asleep.
If you refrigerate apples, they last longer before going bad.
If you keep the curtains closed, then you need less electricity to heat or cool the house (the electric bill is lower).
If you leave a bucket of water uncovered, then it evaporates more quickly.
Goldfish lose their color if they are not exposed to light.
Workers who take vacations are more productive than those who never take time off.

Is It Okay to Disprove a Hypothesis?

Yes! You may even choose to write your hypothesis in such a way that it can be disproved because it’s easier to prove a statement is wrong than to prove it is right. In other cases, if your prediction is incorrect, that doesn’t mean the science is bad. Revising a hypothesis is common. It demonstrates you learned something you did not know before you conducted the experiment.

Test yourself with a Scientific Method Quiz .

Mellenbergh, G.J. (2008). Chapter 8: Research designs: Testing of research hypotheses. In H.J. Adèr & G.J. Mellenbergh (eds.), Advising on Research Methods: A Consultant’s Companion . Huizen, The Netherlands: Johannes van Kessel Publishing.
Popper, Karl R. (1959). The Logic of Scientific Discovery . Hutchinson & Co. ISBN 3-1614-8410-X.
Schick, Theodore; Vaughn, Lewis (2002). How to think about weird things: critical thinking for a New Age . Boston: McGraw-Hill Higher Education. ISBN 0-7674-2048-9.
Tobi, Hilde; Kampen, Jarl K. (2018). “Research design: the methodology for interdisciplinary research framework”. Quality & Quantity . 52 (3): 1209–1225. doi: 10.1007/s11135-017-0513-8

Scientific Method: Step 3: HYPOTHESIS

Step 1: QUESTION
Step 2: RESEARCH
Step 3: HYPOTHESIS
Step 4: EXPERIMENT
Step 5: DATA
Step 6: CONCLUSION

Step 3: State your hypothesis

Now it's time to state your hypothesis . The hypothesis is an educated guess as to what will happen during your experiment.

The hypothesis is often written using the words "IF" and "THEN." For example, " If I do not study, then I will fail the test." The "if' and "then" statements reflect your independent and dependent variables .

The hypothesis should relate back to your original question and must be testable .

A word about variables...

Your experiment will include variables to measure and to explain any cause and effect. Below you will find some useful links describing the different types of variables.

"What are independent and dependent variables" NCES
[VIDEO] Biology: Independent vs. Dependent Variables (Nucleus Medical Media) Video explaining independent and dependent variables, with examples.

Resource Links

What is and How to Write a Good Hypothesis in Research? (Elsevier)
Hypothesis brochure from Penn State/Berks

<< Previous: Step 2: RESEARCH
Next: Step 4: EXPERIMENT >>
Last Updated: Aug 26, 2024 10:04 AM
URL: https://harford.libguides.com/scientific_method

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How to Write a Strong Hypothesis | Guide & Examples

How to Write a Strong Hypothesis | Guide & Examples

Published on 6 May 2022 by Shona McCombes .

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

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

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

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

Variables in hypotheses

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

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

Prevent plagiarism, run a free check.

Step 1: ask a question.

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

Step 2: Do some preliminary research

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

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

Step 3: Formulate your hypothesis

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

Step 4: Refine your hypothesis

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

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

Step 5: Phrase your hypothesis in three ways

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

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

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

Step 6. Write a null hypothesis

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

Research question	Hypothesis	Null hypothesis
What are the health benefits of eating an apple a day?	Increasing apple consumption in over-60s will result in decreasing frequency of doctor’s visits.	Increasing apple consumption in over-60s will have no effect on frequency of doctor’s visits.
Which airlines have the most delays?	Low-cost airlines are more likely to have delays than premium airlines.	Low-cost and premium airlines are equally likely to have delays.
Can flexible work arrangements improve job satisfaction?	Employees who have flexible working hours will report greater job satisfaction than employees who work fixed hours.	There is no relationship between working hour flexibility and job satisfaction.
How effective is secondary school sex education at reducing teen pregnancies?	Teenagers who received sex education lessons throughout secondary school will have lower rates of unplanned pregnancy than teenagers who did not receive any sex education.	Secondary school sex education has no effect on teen pregnancy rates.
What effect does daily use of social media have on the attention span of under-16s?	There is a negative correlation between time spent on social media and attention span in under-16s.	There is no relationship between social media use and attention span in under-16s.

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

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

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

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

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How to Write a Hypothesis [31 Tips + Examples]

Writing hypotheses can seem tricky, but it’s essential for a solid scientific inquiry.

Here is a quick summary of how to write a hypothesis:

Write a hypothesis by clearly defining your research question, identifying independent and dependent variables, formulating a measurable prediction, and ensuring it can be tested through experimentation. Include an “if…then” statement for clarity.

I’ve crafted dozens in my research, from basic biology experiments to business marketing strategies.

Let me walk you through how to write a solid hypothesis, step by step.

Writing a Hypothesis: The Basics

Notebook and scientific diagrams glow amidst dramatic lighting -- How to Write a Hypothesis

Table of Contents

A hypothesis is a statement predicting the relationship between variables based on observations and existing knowledge. To craft a good hypothesis:

Identify variables – Determine the independent and dependent variables involved.
Predict relationships – Predict the interaction between these variables.
Test the statement – Ensure the hypothesis is testable and falsifiable.

A solid hypothesis guides your research and sets the foundation for your experiment.

31 Tips for Writing a Hypothesis

There are at least 31 tips to write a good hypothesis.

Keep reading to learn every tip plus three examples to make sure that you can instantly apply it to your writing.

Tip 1: Start with a Clear Research Question

A clear research question ensures your hypothesis is targeted.

Identify the broad topic you’re curious about, then refine it to a specific question.
Use guiding questions like “What impact does variable X have on variable Y?”
How does fertilizer affect plant growth?
Does social media influence mental health in teens?
Can personalized ads increase customer engagement?

Tip 2: Do Background Research

Research helps you understand current knowledge and any existing gaps.

Review scholarly articles, reputable websites, and textbooks.
Focus on understanding the relationships between variables in existing research.
Academic journals like ScienceDirect or JSTOR.
Google Scholar.
Reputable news articles.

Tip 3: Identify Independent and Dependent Variables

The independent variable is what you change or control. The dependent variable is what you measure.

Clearly define these variables to make your hypothesis precise.
Think of different factors that could be influencing your dependent variable.
Type of fertilizer (independent) and plant growth (dependent).
Amount of screen time (independent) and anxiety levels (dependent).
Marketing strategies (independent) and customer engagement (dependent).

Tip 4: Make Your Hypothesis Testable

A hypothesis must be measurable and falsifiable.

Ensure your hypothesis can be supported or refuted through data collection.
Include numerical variables or qualitative changes to ensure measurability.
“Increasing screen time will increase anxiety levels in teenagers.”
“Using fertilizer X will yield higher crop productivity.”
“A/B testing marketing strategies will show higher engagement with personalized ads.”

Tip 5: Be Specific and Concise

Keep your hypothesis straightforward and to the point.

Avoid vague terms that could mislead or cause confusion.
Clearly outline what you’re measuring and how the variables interact.
“Replacing chemical fertilizers with organic ones will result in slower plant growth.”
“A social media break will decrease anxiety in high school students.”
“Ads targeting user preferences will boost click-through rates by 10%.”

Tip 6: Choose Simple Language

Use simple, understandable language to ensure clarity.

Avoid jargon and overly complex terms that could confuse readers.
Make the hypothesis comprehensible to non-experts in the field.
“Organic fertilizer will reduce plant growth.”
“High schoolers will feel less anxious after a social media detox.”
“Targeted ads will increase customer engagement.”

Tip 7: Formulate a Null Hypothesis

A null hypothesis assumes no relationship between variables.

Create a counterpoint to your main hypothesis, asserting that there is no effect.
This allows you to compare results directly and identify statistical significance.
“Fertilizer type will not affect plant growth.”
“Social media use will not influence anxiety.”
“Targeted ads will not affect customer engagement.”

Tip 8: State Alternative Hypotheses

Provide alternative hypotheses to explore other plausible relationships.

They offer a contingency plan if your primary hypothesis is not supported.
These should still align with your research question and measurable variables.
“Fertilizer X will only affect plant growth if used in specific soil types.”
“Social media might impact anxiety only in certain age groups.”
“Customer engagement might only improve with highly personalized ads.”

Tip 9: Use “If…Then” Statements

“If…then” statements simplify the cause-and-effect structure.

The “if” clause identifies the independent variable, while “then” identifies the dependent.
It makes your hypothesis easier to understand and directly testable.
“If plants receive organic fertilizer, then their growth rate will slow.”
“If teens stop using social media, then their anxiety will decrease.”
“If ads are personalized, then click-through rates will increase.”

Tip 10: Avoid Assumptions

Don’t assume the audience understands your variables or relationships.

Clearly define terms and relationships to avoid misinterpretation.
Provide background context where necessary for clarity.
Define “anxiety” as a feeling of worry or unease.
Specify “plant growth” as the height and health of plants.
Describe “personalized ads” as ads matching user preferences.

Tip 11: Review Existing Literature

Previous research offers insights into forming a hypothesis.

Conduct a thorough literature review to identify trends and gaps.
Use these studies to refine and build upon your hypothesis.
Studies showing a link between screen time and anxiety.
Research on organic versus chemical fertilizers.
Customer behavior analysis in different marketing channels.

Tip 12: Consider Multiple Variables

Hypotheses with multiple variables can offer deeper insights.

Explore combinations of independent and dependent variables to see their relationships.
Plan experiments accordingly to distinguish separate effects.
Studying fertilizer type and soil composition effects on plant growth.
Testing social media use frequency and content type on anxiety.
Analyzing marketing strategies combined with product preferences.

Tip 13: Review Ethical Considerations

Ethics are essential for trustworthy research.

Avoid hypotheses that could cause harm to participants or the environment.
Seek approval from relevant ethical boards or committees.
Avoiding experiments causing undue stress to teenagers.
Preventing chemical contamination when testing fertilizers.
Respecting privacy with personalized ads.

Tip 14: Test with Pilot Studies

Small-scale pilot studies test feasibility and refine hypotheses.

Use them to identify potential issues and adjust before full-scale research.
Ensure pilot tests align with ethical standards.
Testing different fertilizer types on small plant samples.
Trying brief social media breaks with a small group of teens.
Conducting A/B tests on ad personalization with a subset of customers.

Tip 15: Build Hypotheses on Existing Theories

Existing theories provide strong foundations.

Use established frameworks to develop or refine your hypothesis.
Testing theoretical predictions can yield meaningful data.
Applying agricultural theories on soil and crop management.
Using psychology theories on screen addiction and mental health.
Referencing marketing theories like consumer behavior analysis.

Tip 16: Address Real-World Problems

Solve real-world problems through practical hypotheses.

Make sure your research question has relevant, impactful applications.
Focus on everyday challenges where actionable insights can help.
Testing new eco-friendly farming methods.
Reducing anxiety by improving digital wellbeing.
Improving marketing ROI with personalized strategies.

Tip 17: Aim for Clear, Measurable Outcomes

The results should be easy to measure and interpret.

Quantify your dependent variable or use defined qualitative measures.
Avoid overly broad or ambiguous outcomes.
Measuring plant growth as a percentage change in height.
Quantifying anxiety levels through standard surveys.
Tracking click-through rates as a percentage of total views.

Tip 18: Stay Open to Unexpected Results

Not all hypotheses yield expected results.

Be open to learning new insights, even if they contradict your prediction.
Unexpected findings often reveal unique, significant knowledge.
Unexpected fertilizer types boosting growth differently than anticipated.
Screen time affecting anxiety differently across various age groups.
Targeted ads backfiring with specific customer segments.

Tip 19: Keep Hypotheses Relevant

Ensure your hypothesis aligns with the purpose of your research.

Avoid straying from the original question or focusing on tangential issues.
Stick to the research scope to ensure accurate and meaningful data.
Focus on a specific type of fertilizer for plant growth.
Restrict studies to relevant age groups for anxiety research.
Keep marketing hypotheses within the same target customer segment.

Tip 20: Collaborate with Peers

Collaboration strengthens hypothesis development.

Work with colleagues or mentors for valuable feedback.
Peer review helps identify flaws or assumptions in your hypothesis.
Reviewing hypothesis clarity with a lab partner.
Sharing research plans with a mentor to refine focus.
Engaging in academic peer-review groups.

Tip 21: Re-evaluate Hypotheses Periodically

Revising hypotheses ensures relevance.

Update based on new literature, data, or technological advances.
A dynamic approach keeps your research current.
Refining fertilizer studies with recent organic farming research.
Adjusting social media hypotheses for new platforms like TikTok.
Modifying marketing hypotheses based on changing customer preferences.

Tip 22: Develop Compelling Visuals

Illustrating hypotheses can help communicate relationships effectively.

Use diagrams or flowcharts to show how variables interact visually.
Infographics make it easier for others to grasp your research concept.
A flowchart showing fertilizer effects on different plant growth stages.
Diagrams illustrating social media use and its psychological impact.
Infographics depicting how various marketing strategies boost engagement.

Tip 23: Refine Your Data Collection Plan

A solid data collection plan is vital for a testable hypothesis.

Determine the best ways to measure your dependent variable.
Ensure your data collection tools are reliable and accurate.
Using a ruler and image analysis software to measure plant height.
Designing standardized surveys to assess anxiety levels consistently.
Setting up click-through tracking with analytics software.

Tip 24: Focus on Logical Progression

Ensure your hypothesis logically follows your research question.

The relationship between variables should naturally flow from your observations.
Avoid logical leaps that might confuse your reasoning.
Predicting plant growth after observing effects of different fertilizers.
Linking anxiety to social media use based on screen time studies.
Connecting ad personalization with customer behavior data.

Tip 25: Test Against Diverse Samples

Testing across diverse samples ensures broader applicability.

Avoid drawing conclusions from overly narrow sample groups.
Try to include different demographics or subgroups in your testing.
Testing fertilizer effects on multiple plant species.
Including different age groups in anxiety research.
Experimenting with personalized ads across varied customer segments.

Tip 26: Use Control Groups

Control groups provide a baseline for comparison.

Compare your test group with a control group under unchanged conditions.
This allows you to isolate the effect of your independent variable.
Comparing plant growth with organic versus no fertilizer.
Testing anxiety levels with and without social media breaks.
Comparing personalized ads with general marketing content.

Tip 27: Consider Practical Constraints

Work within realistic constraints for your resources and timeline.

Assess the feasibility of testing your hypothesis.
Modify the hypothesis if the required testing is unmanageable.
Reducing fertilizer types to a manageable number for testing.
Shortening social media detox periods to realistic durations.
Targeting only specific marketing strategies to optimize testing.

Tip 28: Recognize Bias Risks

Biases can skew hypothesis formation.

Acknowledge your assumptions and how they may affect your research.
Minimize biases by clearly defining and measuring variables.
Avoiding assumptions that organic fertilizer is inherently better.
Ensuring survey questions don’t lead to specific anxiety outcomes.
Testing marketing strategies objectively without favoring any method.

Tip 29: Prepare for Peer Review

Peer review ensures your hypothesis holds up to scrutiny.

Provide a clear rationale for why your hypothesis is sound.
Address potential criticisms to strengthen your research.
Showing your plant growth study builds on existing fertilizer research.
Demonstrating social media anxiety links through data and literature.
Supporting your marketing hypotheses with solid behavioral data.

Tip 30: Create a Research Proposal

A proposal outlines your hypothesis, methodology, and significance.

It ensures your hypothesis is clear and your methods are well-thought-out.
Proposals also help secure funding or institutional approval.
A proposal for fertilizer studies linking plant growth and soil health.
Research plans connecting social media habits to anxiety measures.
Marketing proposals tying customer behavior to personalized advertising.

Tip 31: Document Your Findings

Recording findings helps validate or challenge your hypothesis.

Document the methodology, data, and conclusions clearly.
This allows others to verify, replicate, or expand on your work.
Recording fertilizer effects on plant height in different soil types.
Survey results linking social media use with anxiety levels.
Click-through data proving personalized ads’ impact on engagement.

Check out this really good video about how to write a hypothesis:

Hypothesis Examples for Different Situations

Let’s look at some examples of how to write a hypothesis in different circumstances.

Marketing Analysis : “If personalized ads are shown to our target demographic, then click-through rates will increase by at least 10%.”
Process Improvement : “If automated workflows replace manual data entry, then task completion times will decrease by 20%.”
Product Development : “If adding a chatbot feature to our app increases customer support efficiency, then user satisfaction will improve by 15%.”
Biology Experiment : “If students grow plants with different fertilizers, then the organic fertilizer will result in slower growth compared to the chemical fertilizer.”
Psychology Research : “If high school students take a break from social media, then their levels of anxiety will decrease.”
Environmental Study : “If a controlled forest area is exposed to a certain pollutant, then the local plant species will show signs of damage within two weeks.”

Professional Contacts

Medical Research : “If a novel treatment method is applied to patients with chronic illness, then their recovery rate will increase significantly compared to standard treatment.”
Technology Research : “If machine learning algorithms analyze big data sets, then the accuracy of predictive models will surpass traditional data analysis.”
Engineering Project : “If new composite materials replace standard components in bridge construction, then the resulting structure will be more durable.”

Super Personal

Gardening Experiment : “If different types of compost are used in home gardens, then plants receiving homemade compost will yield the most produce.”
Fitness Routine : “If consistent strength training is combined with a high-protein diet, then muscle mass will increase more than with diet alone.”
Cooking Techniques : “If searing is added before baking, then the resulting roast will retain more moisture.”

Final Thoughts: How to Write a Hypothesis

Crafting hypotheses is both a science and an art. It’s about channeling curiosity into testable questions that propel meaningful discovery.

Each well-thought-out hypothesis is a stepping stone that could lead to the breakthrough you’ve been seeking.

Stay curious and let your research journey unfold.

How to Write a Hypothesis: Tips, Guidelines, and Hypothesis Examples

In any industry, the ability to use observations and create a compelling hypothesis to solve a problem through research is very valuable. Scientists, data analysts, and medical professionals should all learn how to write a hypothesis to guide their research. A good hypothesis is a key part of using research methods that lead to impactful research.

In this guide, we’ll define a hypothesis and the elements that make a complete hypothesis. We’ll also cover a couple of hypothesis examples and answer questions about creating a hypothesis. By the time you are done reading this article, you’ll know how to write a hypothesis that is perfect for any research project or empirical research paper.

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What is a hypothesis.

A hypothesis is a testable statement used in research, and researchers use the hypothesis to design an experiment that will give results that support or do not support the hypothesis. People make causal hypotheses all the time when solving problems. For example, if you have an assumption that if you restart your computer it will fix the problem you’re having with a program, that statement is testable, because you can restart your computer and see if it fixes the problem.

What Are the Elements of a Hypothesis?

Statement of the research question. A hypothesis is the research question rewritten as a testable statement. You have to include the goal of the research, the variables, the relationship between variables, and a testable prediction. Without a clear research question, you could end up performing endless, aimless research studies.
Independent variable. The independent variable is the part of the experiment where you change something. If you are wondering whether different types of motor oil change your car’s mileage, motor oil is the independent variable. This is usually based on an idea that you came up with to solve a problem.
Dependent variable. The dependent variable is the part of the experiment where you measure the outcome and collect data. In the above example about motor oil, the dependent variable is the car’s mileage because that is what you are measuring.
Predicted relationship between the independent and dependent variable. The goal of your hypothesis is to make an educated guess of what impact the independent variable has on the dependent variable. You can hypothesize that different kinds of motor oil will have no effect on a car’s mileage, or that one kind of motor oil will increase the car’s mileage. This is also the declarative statement.
Testability. You have to be able to test your hypothesis through experimentation. A hypothesis like, “Unicorns prefer to eat cake instead of cookies,” isn’t testable because there aren’t any unicorns to do the experiment with.

How to Write a Hypothesis: Beginning and Ending

To write a solid hypothesis you need to understand the scientific method and the basic format of a hypothesis. A strong, testable hypothesis turns random ideas into scientific experiments. A well-written hypothesis is usually a single sentence. Let’s look at how to start and end a strong hypothesis.

How to Begin a Hypothesis

The beginning of your hypothesis introduces the variables. Remember, the independent variable is the thing you change in your experiment and the dependent variable is the thing you measure. In the example, “Flowers watered with lemonade will grow faster than flowers watered with plain water,” water and lemonade are the independent variables and flowers’ growth rate is the dependent variable.

Many people choose to structure hypotheses as an if-then statement. For instance, “If you drink coffee before going to bed, then it will take you longer to fall asleep.” If you are having trouble with the process of hypothesis writing, then you should try starting with an if-then statement.

How to End a Hypothesis

The second section of a simple hypothesis statement is where you predict the relationship between the types of variables. Using our coffee example above, the second half of the sentence shows how we expect the amount of coffee to impact the time it takes to fall asleep.

When you write your prediction, remember to ask yourself, “Is this hypothesis testable?” You can predict that there is no relationship between your variables, that the independent variable will have an effect on the dependent variable, or you can make a specific guess about how the independent variable will affect the dependent variable. Bad hypotheses are not testable, because there is no way to prove or disprove your original idea.

How to Write a Hypothesis: 5 More Useful Tips

A person writing in a notebook with a light blue pen.

Conduct preliminary research

To create a scientific hypothesis, you need to get background knowledge on your topic by reading previous studies, scientific experiments, and academic journals. You need to become a student of the sciences again. Be open-minded and explore research that supports and doesn’t support your ideas. Learn about the experimental methods other people use, and find any knowledge gaps that you could fill with your research question.

Define a research question

The first step in formulating a hypothesis is to brainstorm a research question. Use your writing skills to write a research question that’s specific, clear, focused, and manageable. Make sure you have the resources to conduct whatever experiment you’ll need to answer the question.

Formulate a hypothesis

Use your new background knowledge to rewrite your research question as a testable statement. Remember to include an independent variable, a dependent variable, and predict how they are related. Use an if-then statement if you are having trouble.

Refine your hypothesis

The first draft of a hypothesis is rarely perfect. You’ll need to edit and proofread to find and fix mistakes. Make sure your hypothesis is testable and has all the relevant variables. Try to get a peer or advisor to read your hypothesis and suggest changes.

Create a null and alternative hypothesis

A null hypothesis always states that there is no relationship between variables, while an alternative hypothesis states there is some kind of relationship between variables. You need to write both a null and alternative hypothesis for statistical analysis. An example of a null hypothesis from our coffee example is, “If you drink coffee before going to bed, it will have no impact on how long it takes to fall asleep.”

Hypothesis Examples to Help You Write a Hypothesis

The best way to learn how to write a hypothesis is to read example hypotheses. Below are a couple of example hypotheses.

Hypothesis Example 1: Smoking and Lung Cancer

A hypothesis explores the relationship between independent and dependent variables. Let’s say we are interested in the relationship between smoking habits and lung cancer. Our independent variable is smoking habits and our dependent variable is lung cancer.

Next, we have to use our hypothesis to make a prediction about the relationship between smoking habits and lung cancer. Based on background knowledge we might guess that daily smoking increases the risk of lung cancer. This is our alternative hypothesis. The null hypothesis requires us to predict that there is no relationship between the variables.

Our null hypothesis is, “Daily smoking does not affect the risk of lung cancer.” Our alternative hypothesis is, “Daily smoking increases the risk of lung cancer.” Both hypotheses have an independent and dependent variable, both are testable, and both predict a relationship between the two variables.

Hypothesis Example 2: Vitamins and Hair Growth Rate

Say you work for a company that distributes vitamins. You think vitamins E and K help hair growth, but there is limited evidence about how these different vitamins impact hair growth. You decide to conduct a single experiment on how vitamins impact hair growth for scientific exploration.

You have a strong research question, “Does vitamin E or vitamin K make your hair grow faster?” Now we need to turn that into an experimental hypothesis. Our independent variable is what vitamins to take and our dependent variable is the hair growth rate. This is a complex hypothesis because we are testing two vitamins, two independent variables.

The null hypothesis is, “Neither vitamin E nor vitamin K impact hair growth rate.” One possible alternative hypothesis is, “Both vitamins E and K increase hair growth rate.” There are also a few other possible alternative hypotheses depending on what you think the relationship is between vitamin E and hair growth vs vitamin K and hair growth.

How to Use Hypothesis Examples to Write Your Own

The hypothesis examples we’ve discussed should give you a starting point for writing your own hypotheses. Use your research skills to develop a research question and then use our tips to rewrite it into a testable hypothesis with a simple prediction.

How to Write a Hypothesis FAQ

A hypothesis is a statement that describes a research question and predicts a relationship between variables. The same information can be posed as a question, but a true hypothesis is written as a statement. Hypotheses are often written as if-then statements.

A null hypothesis is a type of hypothesis that predicts that there is no relationship between your variables. For instance, if your research question is, “Is it important to integrate mental health education into schools?” Your null hypothesis is, “Implementation of mental health education in school will not affect students.

An alternative hypothesis means you expect that there is some relationship between variables. Let’s use the research question, “Is it important to integrate mental health education into schools?” An alternative hypothesis to that would be “Implementing mental health education in school programs will impact students.”

A good hypothesis is a simple statement of a research question that is testable and must include a dependent variable, an independent variable, and a prediction of the relationship between the two variables. There are also specific types of hypotheses such as a directional hypothesis, a non-directional hypothesis, or an associative hypothesis.

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The Craft of Writing a Strong Hypothesis

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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Learn How To Write A Hypothesis For Your Next Research Project!

Undoubtedly, research plays a crucial role in substantiating or refuting our assumptions. These assumptions act as potential answers to our questions. Such assumptions, also known as hypotheses, are considered key aspects of research. In this blog, we delve into the significance of hypotheses. And provide insights on how to write them effectively. So, let’s dive in and explore the art of writing hypotheses together.

Table of Contents

What is a Hypothesis?

A hypothesis is a crucial starting point in scientific research. It is an educated guess about the relationship between two or more variables. In other words, a hypothesis acts as a foundation for a researcher to build their study.

Here are some examples of well-crafted hypotheses:

Increased exposure to natural sunlight improves sleep quality in adults.

A positive relationship between natural sunlight exposure and sleep quality in adult individuals.

Playing puzzle games on a regular basis enhances problem-solving abilities in children.

Engaging in frequent puzzle gameplay leads to improved problem-solving skills in children.

Students and improved learning hecks.

S tudents using online paper writing service platforms (as a learning tool for receiving personalized feedback and guidance) will demonstrate improved writing skills. (compared to those who do not utilize such platforms).

The use of APA format in research papers.

Using the APA format helps students stay organized when writing research papers. Organized students can focus better on their topics and, as a result, produce better quality work.

The Building Blocks of a Hypothesis

To better understand the concept of a hypothesis, let’s break it down into its basic components:

Variables . A hypothesis involves at least two variables. An independent variable and a dependent variable. The independent variable is the one being changed or manipulated, while the dependent variable is the one being measured or observed.
Relationship : A hypothesis proposes a relationship or connection between the variables. This could be a cause-and-effect relationship or a correlation between them.
Testability : A hypothesis should be testable and falsifiable, meaning it can be proven right or wrong through experimentation or observation.

Types of Hypotheses

When learning how to write a hypothesis, it’s essential to understand its main types. These include; alternative hypotheses and null hypotheses. In the following section, we explore both types of hypotheses with examples.

Alternative Hypothesis (H1)

This kind of hypothesis suggests a relationship or effect between the variables. It is the main focus of the study. The researcher wants to either prove or disprove it. Many research divides this hypothesis into two subsections:

Directional

This type of H1 predicts a specific outcome. Many researchers use this hypothesis to explore the relationship between variables rather than the groups.

Non-directional

You can take a guess from the name. This type of H1 does not provide a specific prediction for the research outcome.

Here are some examples for your better understanding of how to write a hypothesis.

Consuming caffeine improves cognitive performance. (This hypothesis predicts that there is a positive relationship between caffeine consumption and cognitive performance.)
Aerobic exercise leads to reduced blood pressure. (This hypothesis suggests that engaging in aerobic exercise results in lower blood pressure readings.)
Exposure to nature reduces stress levels among employees. (Here, the hypothesis proposes that employees exposed to natural environments will experience decreased stress levels.)
Listening to classical music while studying increases memory retention. (This hypothesis speculates that studying with classical music playing in the background boosts students’ ability to retain information.)
Early literacy intervention improves reading skills in children. (This hypothesis claims that providing early literacy assistance to children results in enhanced reading abilities.)
Time management in nursing students. ( Students who use a nursing research paper writing service have more time to focus on their studies and can achieve better grades in other subjects. )

Null Hypothesis (H0)

A null hypothesis assumes no relationship or effect between the variables. If the alternative hypothesis is proven to be false, the null hypothesis is considered to be true. Usually a null hypothesis shows no direct correlation between the defined variables.

Here are some of the examples

The consumption of herbal tea has no effect on sleep quality. (This hypothesis assumes that herbal tea consumption does not impact the quality of sleep.)
The number of hours spent playing video games is unrelated to academic performance. (Here, the null hypothesis suggests that no relationship exists between video gameplay duration and academic achievement.)
Implementing flexible work schedules has no influence on employee job satisfaction. (This hypothesis contends that providing flexible schedules does not affect how satisfied employees are with their jobs.)
Writing ability of a 7th grader is not affected by reading editorial example. ( There is no relationship between reading an editorial example and improving a 7th grader’s writing abilities.)
The type of lighting in a room does not affect people’s mood. (In this null hypothesis, there is no connection between the kind of lighting in a room and the mood of those present.)
The use of social media during break time does not impact productivity at work. (This hypothesis proposes that social media usage during breaks has no effect on work productivity.)

As you learn how to write a hypothesis, remember that aiming for clarity, testability, and relevance to your research question is vital. By mastering this skill, you’re well on your way to conducting impactful scientific research. Good luck!

Importance of a Hypothesis in Research

A well-structured hypothesis is a vital part of any research project for several reasons:

It provides clear direction for the study by setting its focus and purpose.
It outlines expectations of the research, making it easier to measure results.
It helps identify any potential limitations in the study, allowing researchers to refine their approach.

In conclusion, a hypothesis plays a fundamental role in the research process. By understanding its concept and constructing a well-thought-out hypothesis, researchers lay the groundwork for a successful, scientifically sound investigation.

How to Write a Hypothesis?

Here are five steps that you can follow to write an effective hypothesis.

Step 1: Identify Your Research Question

The first step in learning how to compose a hypothesis is to clearly define your research question. This question is the central focus of your study and will help you determine the direction of your hypothesis.

Step 2: Determine the Variables

When exploring how to write a hypothesis, it’s crucial to identify the variables involved in your study. You’ll need at least two variables:

Independent variable : The factor you manipulate or change in your experiment.
Dependent variable : The outcome or result you observe or measure, which is influenced by the independent variable.

Step 3: Build the Hypothetical Relationship

In understanding how to compose a hypothesis, constructing the relationship between the variables is key. Based on your research question and variables, predict the expected outcome or connection. This prediction should be specific, testable, and, if possible, expressed in the “If…then” format.

Step 4: Write the Null Hypothesis

When mastering how to write a hypothesis, it’s important to create a null hypothesis as well. The null hypothesis assumes no relationship or effect between the variables, acting as a counterpoint to your primary hypothesis.

Step 5: Review Your Hypothesis

Finally, when learning how to compose a hypothesis, it’s essential to review your hypothesis for clarity, testability, and relevance to your research question. Make any necessary adjustments to ensure it provides a solid basis for your study.

In conclusion, understanding how to write a hypothesis is crucial for conducting successful scientific research. By focusing on your research question and carefully building relationships between variables, you will lay a strong foundation for advancing research and knowledge in your field.

Hypothesis vs. Prediction: What’s the Difference?

Understanding the differences between a hypothesis and a prediction is crucial in scientific research. Often, these terms are used interchangeably, but they have distinct meanings and functions. This segment aims to clarify these differences and explain how to compose a hypothesis correctly, helping you improve the quality of your research projects.

Hypothesis: The Foundation of Your Research

A hypothesis is an educated guess about the relationship between two or more variables. It provides the basis for your research question and is a starting point for an experiment or observational study.

The critical elements for a hypothesis include:

Specificity: A clear and concise statement that describes the relationship between variables.
Testability: The ability to test the hypothesis through experimentation or observation.

To learn how to write a hypothesis, it’s essential to identify your research question first and then predict the relationship between the variables.

Prediction: The Expected Outcome

A prediction is a statement about a specific outcome you expect to see in your experiment or observational study. It’s derived from the hypothesis and provides a measurable way to test the relationship between variables.

Here’s an example of how to write a hypothesis and a related prediction:

Hypothesis: Consuming a high-sugar diet leads to weight gain.
Prediction: People who consume a high-sugar diet for six weeks will gain more weight than those who maintain a low-sugar diet during the same period.

Key Differences Between a Hypothesis and a Prediction

While a hypothesis and prediction are both essential components of scientific research, there are some key differences to keep in mind:

A hypothesis is an educated guess that suggests a relationship between variables, while a prediction is a specific and measurable outcome based on that hypothesis.
A hypothesis can give rise to multiple experiment or observational study predictions.

To conclude, understanding the differences between a hypothesis and a prediction, and learning how to write a hypothesis, are essential steps to form a robust foundation for your research. By creating clear, testable hypotheses along with specific, measurable predictions, you lay the groundwork for scientifically sound investigations.

Here’s a wrap-up for this guide on how to write a hypothesis. We’re confident this article was helpful for many of you. We understand that many students struggle with writing their school research . However, we hope to continue assisting you through our blog tutorial on writing different aspects of academic assignments.

For further information, you can check out our reverent blog or contact our professionals to avail amazing writing services. Paper perk experts tailor assignments to reflect your unique voice and perspectives. Our professionals make sure to stick around till your satisfaction. So what are you waiting for? Pick your required service and order away!

How to write a good hypothesis?

How to write a hypothesis in science, how to write a research hypothesis, how to write a null hypothesis, what is the format for a scientific hypothesis, how do you structure a proper hypothesis, can you provide an example of a hypothesis, what is the ideal hypothesis structure.

The ideal hypothesis structure includes the following;

A clear statement of the relationship between variables.
testable prediction.
falsifiability.

If your hypothesis has all of these, it is both scientifically sound and effective.

How to write a hypothesis for product management?

Writing a hypothesis for product management involves a simple process:

First, identify the problem or question you want to address.
State your assumption or belief about the solution to that problem. .
Make a hypothesis by predicting a specific outcome based on your assumption.
Make sure your hypothesis is specific, measurable, and testable.
Use experiments, data analysis, or user feedback to validate your hypothesis.
Make informed decisions for product improvement.

Following these steps will help you in effectively formulating hypotheses for product management.

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What Is a Hypothesis and How Do I Write One?

General Education

Think about something strange and unexplainable in your life. Maybe you get a headache right before it rains, or maybe you think your favorite sports team wins when you wear a certain color. If you wanted to see whether these are just coincidences or scientific fact, you would form a hypothesis, then create an experiment to see whether that hypothesis is true or not.

But what is a hypothesis, anyway? If you’re not sure about what a hypothesis is--or how to test for one!--you’re in the right place. This article will teach you everything you need to know about hypotheses, including:

Defining the term “hypothesis”
Providing hypothesis examples
Giving you tips for how to write your own hypothesis

So let’s get started!

What Is a Hypothesis?

Merriam Webster defines a hypothesis as “an assumption or concession made for the sake of argument.” In other words, a hypothesis is an educated guess . Scientists make a reasonable assumption--or a hypothesis--then design an experiment to test whether it’s true or not. Keep in mind that in science, a hypothesis should be testable. You have to be able to design an experiment that tests your hypothesis in order for it to be valid.

As you could assume from that statement, it’s easy to make a bad hypothesis. But when you’re holding an experiment, it’s even more important that your guesses be good...after all, you’re spending time (and maybe money!) to figure out more about your observation. That’s why we refer to a hypothesis as an educated guess--good hypotheses are based on existing data and research to make them as sound as possible.

Hypotheses are one part of what’s called the scientific method . Every (good) experiment or study is based in the scientific method. The scientific method gives order and structure to experiments and ensures that interference from scientists or outside influences does not skew the results. It’s important that you understand the concepts of the scientific method before holding your own experiment. Though it may vary among scientists, the scientific method is generally made up of six steps (in order):

Observation
Asking questions
Forming a hypothesis
Analyze the data
Communicate your results

You’ll notice that the hypothesis comes pretty early on when conducting an experiment. That’s because experiments work best when they’re trying to answer one specific question. And you can’t conduct an experiment until you know what you’re trying to prove!

Independent and Dependent Variables

After doing your research, you’re ready for another important step in forming your hypothesis: identifying variables. Variables are basically any factor that could influence the outcome of your experiment . Variables have to be measurable and related to the topic being studied.

There are two types of variables: independent variables and dependent variables. I ndependent variables remain constant . For example, age is an independent variable; it will stay the same, and researchers can look at different ages to see if it has an effect on the dependent variable.

Speaking of dependent variables... dependent variables are subject to the influence of the independent variable , meaning that they are not constant. Let’s say you want to test whether a person’s age affects how much sleep they need. In that case, the independent variable is age (like we mentioned above), and the dependent variable is how much sleep a person gets.

Variables will be crucial in writing your hypothesis. You need to be able to identify which variable is which, as both the independent and dependent variables will be written into your hypothesis. For instance, in a study about exercise, the independent variable might be the speed at which the respondents walk for thirty minutes, and the dependent variable would be their heart rate. In your study and in your hypothesis, you’re trying to understand the relationship between the two variables.

Elements of a Good Hypothesis

The best hypotheses start by asking the right questions . For instance, if you’ve observed that the grass is greener when it rains twice a week, you could ask what kind of grass it is, what elevation it’s at, and if the grass across the street responds to rain in the same way. Any of these questions could become the backbone of experiments to test why the grass gets greener when it rains fairly frequently.

As you’re asking more questions about your first observation, make sure you’re also making more observations . If it doesn’t rain for two weeks and the grass still looks green, that’s an important observation that could influence your hypothesis. You'll continue observing all throughout your experiment, but until the hypothesis is finalized, every observation should be noted.

Finally, you should consult secondary research before writing your hypothesis . Secondary research is comprised of results found and published by other people. You can usually find this information online or at your library. Additionally, m ake sure the research you find is credible and related to your topic. If you’re studying the correlation between rain and grass growth, it would help you to research rain patterns over the past twenty years for your county, published by a local agricultural association. You should also research the types of grass common in your area, the type of grass in your lawn, and whether anyone else has conducted experiments about your hypothesis. Also be sure you’re checking the quality of your research . Research done by a middle school student about what minerals can be found in rainwater would be less useful than an article published by a local university.

Writing Your Hypothesis

Once you’ve considered all of the factors above, you’re ready to start writing your hypothesis. Hypotheses usually take a certain form when they’re written out in a research report.

When you boil down your hypothesis statement, you are writing down your best guess and not the question at hand . This means that your statement should be written as if it is fact already, even though you are simply testing it.

The reason for this is that, after you have completed your study, you'll either accept or reject your if-then or your null hypothesis. All hypothesis testing examples should be measurable and able to be confirmed or denied. You cannot confirm a question, only a statement!

In fact, you come up with hypothesis examples all the time! For instance, when you guess on the outcome of a basketball game, you don’t say, “Will the Miami Heat beat the Boston Celtics?” but instead, “I think the Miami Heat will beat the Boston Celtics.” You state it as if it is already true, even if it turns out you’re wrong. You do the same thing when writing your hypothesis.

Additionally, keep in mind that hypotheses can range from very specific to very broad. These hypotheses can be specific, but if your hypothesis testing examples involve a broad range of causes and effects, your hypothesis can also be broad.

The Two Types of Hypotheses

Now that you understand what goes into a hypothesis, it’s time to look more closely at the two most common types of hypothesis: the if-then hypothesis and the null hypothesis.

#1: If-Then Hypotheses

First of all, if-then hypotheses typically follow this formula:

If ____ happens, then ____ will happen.

The goal of this type of hypothesis is to test the causal relationship between the independent and dependent variable. It’s fairly simple, and each hypothesis can vary in how detailed it can be. We create if-then hypotheses all the time with our daily predictions. Here are some examples of hypotheses that use an if-then structure from daily life:

If I get enough sleep, I’ll be able to get more work done tomorrow.
If the bus is on time, I can make it to my friend’s birthday party.
If I study every night this week, I’ll get a better grade on my exam.

In each of these situations, you’re making a guess on how an independent variable (sleep, time, or studying) will affect a dependent variable (the amount of work you can do, making it to a party on time, or getting better grades).

You may still be asking, “What is an example of a hypothesis used in scientific research?” Take one of the hypothesis examples from a real-world study on whether using technology before bed affects children’s sleep patterns. The hypothesis read s:

“We hypothesized that increased hours of tablet- and phone-based screen time at bedtime would be inversely correlated with sleep quality and child attention.”

It might not look like it, but this is an if-then statement. The researchers basically said, “If children have more screen usage at bedtime, then their quality of sleep and attention will be worse.” The sleep quality and attention are the dependent variables and the screen usage is the independent variable. (Usually, the independent variable comes after the “if” and the dependent variable comes after the “then,” as it is the independent variable that affects the dependent variable.) This is an excellent example of how flexible hypothesis statements can be, as long as the general idea of “if-then” and the independent and dependent variables are present.

#2: Null Hypotheses

Your if-then hypothesis is not the only one needed to complete a successful experiment, however. You also need a null hypothesis to test it against. In its most basic form, the null hypothesis is the opposite of your if-then hypothesis . When you write your null hypothesis, you are writing a hypothesis that suggests that your guess is not true, and that the independent and dependent variables have no relationship .

One null hypothesis for the cell phone and sleep study from the last section might say:

“If children have more screen usage at bedtime, their quality of sleep and attention will not be worse.”

In this case, this is a null hypothesis because it’s asking the opposite of the original thesis!

Conversely, if your if-then hypothesis suggests that your two variables have no relationship, then your null hypothesis would suggest that there is one. So, pretend that there is a study that is asking the question, “Does the amount of followers on Instagram influence how long people spend on the app?” The independent variable is the amount of followers, and the dependent variable is the time spent. But if you, as the researcher, don’t think there is a relationship between the number of followers and time spent, you might write an if-then hypothesis that reads:

“If people have many followers on Instagram, they will not spend more time on the app than people who have less.”

In this case, the if-then suggests there isn’t a relationship between the variables. In that case, one of the null hypothesis examples might say:

“If people have many followers on Instagram, they will spend more time on the app than people who have less.”

You then test both the if-then and the null hypothesis to gauge if there is a relationship between the variables, and if so, how much of a relationship.

4 Tips to Write the Best Hypothesis

If you’re going to take the time to hold an experiment, whether in school or by yourself, you’re also going to want to take the time to make sure your hypothesis is a good one. The best hypotheses have four major elements in common: plausibility, defined concepts, observability, and general explanation.

#1: Plausibility

At first glance, this quality of a hypothesis might seem obvious. When your hypothesis is plausible, that means it’s possible given what we know about science and general common sense. However, improbable hypotheses are more common than you might think.

Imagine you’re studying weight gain and television watching habits. If you hypothesize that people who watch more than twenty hours of television a week will gain two hundred pounds or more over the course of a year, this might be improbable (though it’s potentially possible). Consequently, c ommon sense can tell us the results of the study before the study even begins.

Improbable hypotheses generally go against science, as well. Take this hypothesis example:

“If a person smokes one cigarette a day, then they will have lungs just as healthy as the average person’s.”

This hypothesis is obviously untrue, as studies have shown again and again that cigarettes negatively affect lung health. You must be careful that your hypotheses do not reflect your own personal opinion more than they do scientifically-supported findings. This plausibility points to the necessity of research before the hypothesis is written to make sure that your hypothesis has not already been disproven.

#2: Defined Concepts

The more advanced you are in your studies, the more likely that the terms you’re using in your hypothesis are specific to a limited set of knowledge. One of the hypothesis testing examples might include the readability of printed text in newspapers, where you might use words like “kerning” and “x-height.” Unless your readers have a background in graphic design, it’s likely that they won’t know what you mean by these terms. Thus, it’s important to either write what they mean in the hypothesis itself or in the report before the hypothesis.

Here’s what we mean. Which of the following sentences makes more sense to the common person?

If the kerning is greater than average, more words will be read per minute.

If the space between letters is greater than average, more words will be read per minute.

For people reading your report that are not experts in typography, simply adding a few more words will be helpful in clarifying exactly what the experiment is all about. It’s always a good idea to make your research and findings as accessible as possible.

Good hypotheses ensure that you can observe the results.

#3: Observability

In order to measure the truth or falsity of your hypothesis, you must be able to see your variables and the way they interact. For instance, if your hypothesis is that the flight patterns of satellites affect the strength of certain television signals, yet you don’t have a telescope to view the satellites or a television to monitor the signal strength, you cannot properly observe your hypothesis and thus cannot continue your study.

Some variables may seem easy to observe, but if you do not have a system of measurement in place, you cannot observe your hypothesis properly. Here’s an example: if you’re experimenting on the effect of healthy food on overall happiness, but you don’t have a way to monitor and measure what “overall happiness” means, your results will not reflect the truth. Monitoring how often someone smiles for a whole day is not reasonably observable, but having the participants state how happy they feel on a scale of one to ten is more observable.

In writing your hypothesis, always keep in mind how you'll execute the experiment.

#4: Generalizability

Perhaps you’d like to study what color your best friend wears the most often by observing and documenting the colors she wears each day of the week. This might be fun information for her and you to know, but beyond you two, there aren’t many people who could benefit from this experiment. When you start an experiment, you should note how generalizable your findings may be if they are confirmed. Generalizability is basically how common a particular phenomenon is to other people’s everyday life.

Let’s say you’re asking a question about the health benefits of eating an apple for one day only, you need to realize that the experiment may be too specific to be helpful. It does not help to explain a phenomenon that many people experience. If you find yourself with too specific of a hypothesis, go back to asking the big question: what is it that you want to know, and what do you think will happen between your two variables?

Hypothesis Testing Examples

We know it can be hard to write a good hypothesis unless you’ve seen some good hypothesis examples. We’ve included four hypothesis examples based on some made-up experiments. Use these as templates or launch pads for coming up with your own hypotheses.

Experiment #1: Students Studying Outside (Writing a Hypothesis)

You are a student at PrepScholar University. When you walk around campus, you notice that, when the temperature is above 60 degrees, more students study in the quad. You want to know when your fellow students are more likely to study outside. With this information, how do you make the best hypothesis possible?

You must remember to make additional observations and do secondary research before writing your hypothesis. In doing so, you notice that no one studies outside when it’s 75 degrees and raining, so this should be included in your experiment. Also, studies done on the topic beforehand suggested that students are more likely to study in temperatures less than 85 degrees. With this in mind, you feel confident that you can identify your variables and write your hypotheses:

If-then: “If the temperature in Fahrenheit is less than 60 degrees, significantly fewer students will study outside.”

Null: “If the temperature in Fahrenheit is less than 60 degrees, the same number of students will study outside as when it is more than 60 degrees.”

These hypotheses are plausible, as the temperatures are reasonably within the bounds of what is possible. The number of people in the quad is also easily observable. It is also not a phenomenon specific to only one person or at one time, but instead can explain a phenomenon for a broader group of people.

To complete this experiment, you pick the month of October to observe the quad. Every day (except on the days where it’s raining)from 3 to 4 PM, when most classes have released for the day, you observe how many people are on the quad. You measure how many people come and how many leave. You also write down the temperature on the hour.

After writing down all of your observations and putting them on a graph, you find that the most students study on the quad when it is 70 degrees outside, and that the number of students drops a lot once the temperature reaches 60 degrees or below. In this case, your research report would state that you accept or “failed to reject” your first hypothesis with your findings.

Experiment #2: The Cupcake Store (Forming a Simple Experiment)

Let’s say that you work at a bakery. You specialize in cupcakes, and you make only two colors of frosting: yellow and purple. You want to know what kind of customers are more likely to buy what kind of cupcake, so you set up an experiment. Your independent variable is the customer’s gender, and the dependent variable is the color of the frosting. What is an example of a hypothesis that might answer the question of this study?

Here’s what your hypotheses might look like:

If-then: “If customers’ gender is female, then they will buy more yellow cupcakes than purple cupcakes.”

Null: “If customers’ gender is female, then they will be just as likely to buy purple cupcakes as yellow cupcakes.”

This is a pretty simple experiment! It passes the test of plausibility (there could easily be a difference), defined concepts (there’s nothing complicated about cupcakes!), observability (both color and gender can be easily observed), and general explanation ( this would potentially help you make better business decisions ).

Experiment #3: Backyard Bird Feeders (Integrating Multiple Variables and Rejecting the If-Then Hypothesis)

While watching your backyard bird feeder, you realized that different birds come on the days when you change the types of seeds. You decide that you want to see more cardinals in your backyard, so you decide to see what type of food they like the best and set up an experiment.

However, one morning, you notice that, while some cardinals are present, blue jays are eating out of your backyard feeder filled with millet. You decide that, of all of the other birds, you would like to see the blue jays the least. This means you'll have more than one variable in your hypothesis. Your new hypotheses might look like this:

If-then: “If sunflower seeds are placed in the bird feeders, then more cardinals will come than blue jays. If millet is placed in the bird feeders, then more blue jays will come than cardinals.”

Null: “If either sunflower seeds or millet are placed in the bird, equal numbers of cardinals and blue jays will come.”

Through simple observation, you actually find that cardinals come as often as blue jays when sunflower seeds or millet is in the bird feeder. In this case, you would reject your “if-then” hypothesis and “fail to reject” your null hypothesis . You cannot accept your first hypothesis, because it’s clearly not true. Instead you found that there was actually no relation between your different variables. Consequently, you would need to run more experiments with different variables to see if the new variables impact the results.

Experiment #4: In-Class Survey (Including an Alternative Hypothesis)

You’re about to give a speech in one of your classes about the importance of paying attention. You want to take this opportunity to test a hypothesis you’ve had for a while:

If-then: If students sit in the first two rows of the classroom, then they will listen better than students who do not.

Null: If students sit in the first two rows of the classroom, then they will not listen better or worse than students who do not.

You give your speech and then ask your teacher if you can hand out a short survey to the class. On the survey, you’ve included questions about some of the topics you talked about. When you get back the results, you’re surprised to see that not only do the students in the first two rows not pay better attention, but they also scored worse than students in other parts of the classroom! Here, both your if-then and your null hypotheses are not representative of your findings. What do you do?

This is when you reject both your if-then and null hypotheses and instead create an alternative hypothesis . This type of hypothesis is used in the rare circumstance that neither of your hypotheses is able to capture your findings . Now you can use what you’ve learned to draft new hypotheses and test again!

Key Takeaways: Hypothesis Writing

The more comfortable you become with writing hypotheses, the better they will become. The structure of hypotheses is flexible and may need to be changed depending on what topic you are studying. The most important thing to remember is the purpose of your hypothesis and the difference between the if-then and the null . From there, in forming your hypothesis, you should constantly be asking questions, making observations, doing secondary research, and considering your variables. After you have written your hypothesis, be sure to edit it so that it is plausible, clearly defined, observable, and helpful in explaining a general phenomenon.

Writing a hypothesis is something that everyone, from elementary school children competing in a science fair to professional scientists in a lab, needs to know how to do. Hypotheses are vital in experiments and in properly executing the scientific method . When done correctly, hypotheses will set up your studies for success and help you to understand the world a little better, one experiment at a time.

What’s Next?

If you’re studying for the science portion of the ACT, there’s definitely a lot you need to know. We’ve got the tools to help, though! Start by checking out our ultimate study guide for the ACT Science subject test. Once you read through that, be sure to download our recommended ACT Science practice tests , since they’re one of the most foolproof ways to improve your score. (And don’t forget to check out our expert guide book , too.)

If you love science and want to major in a scientific field, you should start preparing in high school . Here are the science classes you should take to set yourself up for success.

If you’re trying to think of science experiments you can do for class (or for a science fair!), here’s a list of 37 awesome science experiments you can do at home

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

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

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

There are 5 main steps in hypothesis testing:

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

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

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

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

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

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

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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

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

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

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What Are Examples of a Hypothesis?

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A hypothesis is an explanation for a set of observations. Hypothesis examples can help you understand how this scientific method works.

Although you could state a scientific hypothesis in various ways, most hypotheses are either "If, then" statements or forms of the null hypothesis. The null hypothesis is sometimes called the "no difference" hypothesis. The null hypothesis is good for experimentation because it's simple to disprove. If you disprove a null hypothesis, that is evidence for a relationship between the variables you are examining.

Hypotheses Examples: Null

All daisies have the same number of petals.
Hyperactivity is unrelated to eating sugar.
The number of pets in a household is unrelated to the number of people living in it.
A person's preference for a shirt is unrelated to its color.

Hypotheses Examples: If, Then

If you get at least 6 hours of sleep, you will do better on tests than if you get less sleep.
If you drop a ball, it will fall toward the ground.
If you drink coffee before going to bed, then it will take longer to fall asleep.
If you cover a wound with a bandage, then it will heal with less scarring.

Improving a Hypothesis to Make It Testable

You may wish to revise your first hypothesis to make it easier to design an experiment to test. For example, let's say you have a bad breakout the morning after eating a lot of greasy food. You may wonder if there is a correlation between eating greasy food and getting pimples. You propose the hypothesis example:

Eating greasy food causes pimples.

Next, you need to design an experiment to test this hypothesis. Let's say you decide to eat greasy food every day for a week and record the effect on your face. Then, as a control, you'll avoid greasy food for the next week and see what happens. Now, this is not a good experiment because it does not take into account other factors such as hormone levels, stress, sun exposure, exercise, or any number of other variables that might conceivably affect your skin.

The problem is that you cannot assign cause to your effect . If you eat french fries for a week and suffer a breakout, can you definitely say it was the grease in the food that caused it? Maybe it was the salt. Maybe it was the potato. Maybe it was unrelated to diet. You can't prove your hypothesis. It's much easier to disprove a hypothesis.

So, let's restate the hypothesis to make it easier to evaluate the data:

Getting pimples is unaffected by eating greasy food.

So, if you eat fatty food every day for a week and suffer breakouts and then don't break out the week that you avoid greasy food, you can be pretty sure something is up. Can you disprove the hypothesis? Probably not, since it is so hard to assign cause and effect. However, you can make a strong case that there is some relationship between diet and acne.

If your skin stays clear for the entire test, you may decide to accept your hypothesis . Again, you didn't prove or disprove anything, which is fine

Null Hypothesis Examples
The Role of a Controlled Variable in an Experiment
Random Error vs. Systematic Error
What Is a Testable Hypothesis?
What Are the Elements of a Good Hypothesis?
Scientific Hypothesis Examples
What Is a Hypothesis? (Science)
Scientific Method Vocabulary Terms
Scientific Method Flow Chart
Understanding Simple vs Controlled Experiments
Six Steps of the Scientific Method
What Is an Experimental Constant?
What Is the Difference Between a Control Variable and Control Group?
Scientific Variable
What Is a Controlled Experiment?
DRY MIX Experiment Variables Acronym

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5.2 - writing hypotheses.

The first step in conducting a hypothesis test is to write the hypothesis statements that are going to be tested. For each test you will have a null hypothesis ($H_0$) and an alternative hypothesis ($H_a$).

When writing hypotheses there are three things that we need to know: (1) the parameter that we are testing (2) the direction of the test (non-directional, right-tailed or left-tailed), and (3) the value of the hypothesized parameter.

At this point we can write hypotheses for a single mean ($\mu$), paired means($\mu_d$), a single proportion ($p$), the difference between two independent means ($\mu_1-\mu_2$), the difference between two proportions ($p_1-p_2$), a simple linear regression slope ($\beta$), and a correlation ($\rho$).
The research question will give us the information necessary to determine if the test is two-tailed (e.g., "different from," "not equal to"), right-tailed (e.g., "greater than," "more than"), or left-tailed (e.g., "less than," "fewer than").
The research question will also give us the hypothesized parameter value. This is the number that goes in the hypothesis statements (i.e., $\mu_0$ and $p_0$). For the difference between two groups, regression, and correlation, this value is typically 0.

Hypotheses are always written in terms of population parameters (e.g., $p$ and $\mu$). The tables below display all of the possible hypotheses for the parameters that we have learned thus far. Note that the null hypothesis always includes the equality (i.e., =).

One Group Mean
Research Question	Is the population mean different from $ \mu_{0} $?	Is the population mean greater than $\mu_{0}$?	Is the population mean less than $\mu_{0}$?
Null Hypothesis, $H_{0}$	$\mu=\mu_{0} $	$\mu=\mu_{0} $	$\mu=\mu_{0} $
Alternative Hypothesis, $H_{a}$	$\mu\neq \mu_{0} $	$\mu> \mu_{0} $	$\mu<\mu_{0} $
Type of Hypothesis Test	Two-tailed, non-directional	Right-tailed, directional	Left-tailed, directional

Paired Means
Research Question	Is there a difference in the population?	Is there a mean increase in the population?	Is there a mean decrease in the population?
Null Hypothesis, $H_{0}$	$\mu_d=0 $	$\mu_d =0 $	$\mu_d=0 $
Alternative Hypothesis, $H_{a}$	$\mu_d \neq 0 $	$\mu_d> 0 $	$\mu_d<0 $
Type of Hypothesis Test	Two-tailed, non-directional	Right-tailed, directional	Left-tailed, directional

One Group Proportion
Research Question	Is the population proportion different from $p_0$?	Is the population proportion greater than $p_0$?	Is the population proportion less than $p_0$?
Null Hypothesis, $H_{0}$	$p=p_0$	$p= p_0$	$p= p_0$
Alternative Hypothesis, $H_{a}$	$p\neq p_0$	$p> p_0$	$p< p_0$
Type of Hypothesis Test	Two-tailed, non-directional	Right-tailed, directional	Left-tailed, directional

Difference between Two Independent Means
Research Question	Are the population means different?	Is the population mean in group 1 greater than the population mean in group 2?	Is the population mean in group 1 less than the population mean in groups 2?
Null Hypothesis, $H_{0}$	$\mu_1=\mu_2$	$\mu_1 = \mu_2 $	$\mu_1 = \mu_2 $
Alternative Hypothesis, $H_{a}$	$\mu_1 \ne \mu_2 $	$\mu_1 \gt \mu_2 $	$\mu_1 \lt \mu_2$
Type of Hypothesis Test	Two-tailed, non-directional	Right-tailed, directional	Left-tailed, directional

Difference between Two Proportions
Research Question	Are the population proportions different?	Is the population proportion in group 1 greater than the population proportion in groups 2?	Is the population proportion in group 1 less than the population proportion in group 2?
Null Hypothesis, $H_{0}$	$p_1 = p_2 $	$p_1 = p_2 $	$p_1 = p_2 $
Alternative Hypothesis, $H_{a}$	$p_1 \ne p_2$	$p_1 \gt p_2 $	$p_1 \lt p_2$
Type of Hypothesis Test	Two-tailed, non-directional	Right-tailed, directional	Left-tailed, directional

Simple Linear Regression: Slope
Research Question	Is the slope in the population different from 0?	Is the slope in the population positive?	Is the slope in the population negative?
Null Hypothesis, $H_{0}$	$\beta =0$	$\beta= 0$	$\beta = 0$
Alternative Hypothesis, $H_{a}$	$\beta\neq 0$	$\beta> 0$	$\beta< 0$
Type of Hypothesis Test	Two-tailed, non-directional	Right-tailed, directional	Left-tailed, directional

Correlation (Pearson's )
Research Question	Is the correlation in the population different from 0?	Is the correlation in the population positive?	Is the correlation in the population negative?
Null Hypothesis, $H_{0}$	$\rho=0$	$\rho= 0$	$\rho = 0$
Alternative Hypothesis, $H_{a}$	$\rho \neq 0$	$\rho > 0$	$\rho< 0$
Type of Hypothesis Test	Two-tailed, non-directional	Right-tailed, directional	Left-tailed, directional

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How to Understand ‘If-Then’ Conditional Statements: A Comprehensive Guide

In math, and even in everyday life, we often say 'if this, then that.' This is the essence of conditional statements. They set up a condition and then describe what happens if that condition is met. For instance, 'If it rains, then the ground gets wet.' These statements are foundational in math, helping us build logical arguments and solve problems. In this guide, we'll dive into the clear-cut world of conditional statements, breaking them down in both simple terms and their mathematical significance.

Step-by-step Guide: Conditional Statements

Defining Conditional Statements: A conditional statement is a logical statement that has two parts: a hypothesis (the ‘if’ part) and a conclusion (the ‘then’ part). Written symbolically, it takes the form: $ \text{If } p, \text{ then } q $ Where $ p $ is the hypothesis and $ q $ is the conclusion.

Truth Values: A conditional statement is either true or false. The only time a conditional statement is false is when the hypothesis is true, but the conclusion is false.

Converse, Inverse, and Contrapositive: 1. Converse: The converse of a conditional statement switches the hypothesis and the conclusion. For the statement “If $ p $, then $ q $”, the converse is “If $ q $, then $ p $”.

2. Inverse: The inverse of a conditional statement negates both the hypothesis and the conclusion. For the statement “If $ p $, then $ q $”, the inverse is “If not $ p $, then not $ q $”.

3. Contrapositive: The contrapositive of a conditional statement switches and negates both the hypothesis and the conclusion. For the statement “If $ p $, then $ q $”, the contrapositive is “If not $ q $, then not $ p $”.

Example 1: Simple Conditional Statement: “If it is raining, then the ground is wet.”

Solution: Hypothesis $( p )$: It is raining. Conclusion $( q )$: The ground is wet.

Example 2: Determining Truth Value Statement: “If a shape has four sides, then it is a rectangle.”

Solution: This statement is false because a shape with four sides could be a square, trapezoid, or other quadrilateral, not necessarily a rectangle.

Example 3: Converse, Inverse, and Contrapositive Statement: “If a number is even, then it is divisible by $2$.”

Solution: Converse: If a number is divisible by $2$, then it is even. Inverse: If a number is not even, then it is not divisible by $2$. Contrapositive: If a number is not divisible by $2$, then it is not even.

Practice Questions:

Write the converse, inverse, and contrapositive for the statement: “If a bird is a penguin, then it cannot fly.”
Determine the truth value of the statement: “If a shape has three sides, then it is a triangle.”
For the statement “If an animal is a cat, then it is a mammal,” which of the following is its converse? a) If an animal is a mammal, then it is a cat. b) If an animal is not a cat, then it is not a mammal. c) If an animal is not a mammal, then it is not a cat.
Converse: If a bird cannot fly, then it is a penguin. Inverse: If a bird is not a penguin, then it can fly. Contrapositive: If a bird can fly, then it is not a penguin.
The statement is true. A shape with three sides is defined as a triangle.
a) If an animal is a mammal, then it is a cat.

by: Effortless Math Team about 11 months ago (category: Articles )

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How Do You Write a Hypothesis?

A hypothesis is a clear, testable statement. It includes a forecast or prediction based on the assumption. Unlike an idea or open question, which are generally vague or speculative, a hypothesis is a precise, verifiable proposition that outlines both the action and expected outcome.

There are several different formats that Scrum Teams can use to write a hypothesis, including:

We believe that [specific change or feature] will result in [desired outcome], because [reasoning behind the change].
Example(s): "We believe that introducing personalized recommendations will increase user engagement by 20%, because users prefer content that matches their interest.”
If we [introduce a feature/change], then [proto-persona] will [expected action], resulting in [benefit].

Example(s): "If we add a customer feedback form to the website, then users will provide more insights, resulting in better product improvements." "If we implement a loyalty rewards program, then frequent shoppers will increase their purchase frequency by 35%, resulting in higher overall sales by 15% and improved customer retention by 10%."

( While not every hypothesis needs to include a number or percentage, doing so makes the hypothesis more focused and specific in what you are testing. Incorporate numbers or percentages when you would like to define the expected results clearly.)

We believe that by [specific change in UI/UX], users will [desired user behavior], because [reasoning related to user experience].
Example(s): “We believe that by simplifying the navigation menu, users will find what they need 25% faster, because the interface will be more intuitive.”
If [action or change], then [user segment] will [behavior], leading to [outcome].
Example: "If we send daily notifications, then frequent users of our calorie tracking app will increase their session frequency by 25%, leading to an 15% increase in overall app usage for users to monitor their daily calorie intake for weight gain/loss.”

Hypotheses can be market-related or testing user adoption.

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Lesson 10 of 10 By Pulkit Jain

An 'IF THEN' statement in SQL is a conditional control flow mechanism that allows you to execute specific codes based on whether a specified condition is met. It's commonly used within procedural SQL languages, PL/SQL or T-SQL , rather than standard SQL. When the 'IF' clause condition is true, the code block following the 'THEN' keyword is executed. If the condition is false, the code block is skipped. It's important to consider that using 'IF THEN' statements can impact the performance of your SQL scripts, especially when dealing with large datasets. This control structure helps implement logic that depends on specific conditions, making your SQL scripts more dynamic and responsive to varying data scenarios.

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Let us look at the control-of-flow statements briefly:

1. IF THEN: The IF THEN statement executes the part of the code when the condition specified with the IF statement is evaluated as true. It does not provide any course of action if the condition remains false.

2. IF ELSE: If the condition is evaluated as true, the IF ELSE statement executes the sequence of statements inside the IF statement . The statements enclosed inside the ELSE block get executed when the condition is false.

3. WHILE: The WHILE statement executes the code block if the condition is satisfied. It repeats until the condition evaluates as false.

4. CASE: The CASE statement is applicable when we have multiple conditions to check for a program code. It also allows numerous actions based on various conditions.

5. BEGIN…END: This BEGIN…END block of code allows multiple statements to be grouped, which helps execute the control-of-flow statements.

6. GOTO: This statement differs slightly from the IF ELSE statements. It also checks the conditions first. If satisfied, the program control jumps to a code block specified by the GOTO keyword.

7. TRY…CATCH: The TRY keyword contains the part of the code where errors are possible. If it gets an error, the program control shifts to CATCH, where the sequence of statements to rectify the problem is defined.

8. BREAK: BREAK is often used with loops and conditional statements . It allows the program control to exit the containing block or terminate a given loop.

9. CONTINUE: Used often with the loops, the CONTINUE statement allows you to skip the code and move to the next iteration.

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IF THEN statement in SQL

The IF THEN statement is part of the control statements in SQL. Simply put, it helps in decision-making and directs program control flow.

The IF statement associates a condition, and then a sequence of statements follows. If the condition is evaluated as accurate, the statements enclosed within the keywords THEN and END IF get executed. If the condition specified is evaluated as false, the statements don't get executed, and the program does nothing.

Syntax of IF THEN statement

Pl/sql (oracle), t-sql (sql server).

In both cases:

‘condition’ is an expression that is evaluated as true or false.
The statements within the THEN or BEGIN block are executed only if the condition is true.
You can extend this syntax with ELSE and ELSEIF for additional conditional logic.

Examples of IF THEN Statements

Here are examples of IF THEN statements in both PL/SQL (Oracle) and T-SQL (SQL Server):

Explanation

In this example, if the salary exceeds 40,000, the bonus is set to 1,000. The DBMS_OUTPUT.PUT_LINE procedure then prints the bonus.

In this T-SQL example, if the @salary exceeds 40,000, the @bonus is set to 1,000. The PRINT statement then outputs the bonus.

Example with ELSE (Both PL/SQL and T-SQL)

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The IF THEN statement in SQL is a powerful tool for implementing conditional logic within your database procedures. It allows you to control the flow of your SQL scripts based on specific conditions, making your operations more dynamic and adaptable. Whether you're working in Oracle's PL/SQL or SQL Server's T-SQL, mastering conditional statements like IF THEN is essential for efficient database management and complex query building.

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1. Can I use the IF THEN statement with SELECT queries?

The IF THEN statement in standard SQL is not directly used within SELECT queries. However, you can achieve similar conditional logic within a SELECT statement using functions like CASE or IF (in MySQL).

2. What are some common use cases for the IF THEN statement in SQL?

The IF THEN statement in SQL, particularly in procedural extensions like PL/SQL (Oracle) and T-SQL (SQL Server), is commonly used in various scenarios to control logic flow based on conditions. Here are some common use cases:

Data Validation
Conditional Data Processing
Error Handling
Complex Business Logic
Conditional Execution of SQL Statements
Dynamic Query Building
Trigger Actions
Conditional Logging

3. Can I nest IF THEN statements in SQL?

Yes, you can nest IF THEN statements in SQL, particularly in procedural SQL languages like PL/SQL (Oracle) and T-SQL (SQL Server). Nesting IF THEN statements allows you to evaluate multiple conditions hierarchically, where the execution of one IF THEN block depends on the outcome of another.

4. Can IF THEN statements be executed in stored procedures?

Yes, IF THEN statements can be executed within stored procedures in SQL, particularly in procedural extensions like PL/SQL (Oracle) and T-SQL (SQL Server). In stored procedures, IF THEN statements are commonly used to control the logic flow, allowing the procedure to perform different actions based on specific conditions.

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About the Author

Pulkit Jain is a Product Manager for Salesforce & Payments at Simplilearn, where he drives impactful product launches and updates. With deep expertise in CRM, cloud & DevOps, and product marketing, Pulkit has a proven track record in steering software development and innovation.

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PDF How to Write a Good Hypothesis Using "If… Then… Because…"
If some students eat breakfast before school and others do not, then the ones who do eat breakfast will have better grades in their morning classes, because their brains have more energy to think. Now, let's try this together. To warm up, identify the three types of variables below. Then use the variables to make a good hypothesis. 1.
How to Write a Hypothesis in 6 Steps, With Examples
When writing a hypothesis, it helps to phrase it using an if-then format, such as, " If I water a plant every day, then it will grow better." This format can get tricky when dealing with multiple variables, but in general, it's a reliable method for expressing the cause-and-effect relationship you're testing. 5 Collect data to support ...
Hypothesis If Then
The "If-Then" hypothesis is a predictive statement that sets up a cause-and-effect relationship between two variables. It's structured such that the "If" portion introduces a condition or a cause, and the "Then" portion predicts the effect or outcome of that condition. This format helps in clearly establishing a link between the ...
How to Write a Strong Hypothesis
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. If a first-year student starts attending more lectures, then their exam scores will improve.
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Learning how to write a hypothesis comes down to knowledge and strategy. So where do you start? ... hypothesis needs to be a statement, not a question. It's an idea, proposal or prediction. For example, a research hypothesis is formatted in an if/then statement: If a person gets less than eight hours of sleep, then they will be less motivated ...
Hypotheses
How to Write a Hypothesis. A hypothesis is a statement. Avoid conditional terms like should, might or could. A hypothesis can be phrased in an if/then format, Ex. if you use Topical Treatment A for male pattern baldness, then you will see a 50% increase in hair grown within 3 months. Another workable structure is when x, then y.
Step-by-Step Guide: How to Craft a Strong Research Hypothesis
A hypothesis can use the if/then format when it seeks to explore the correlation between two variables in a study primarily. Example: If administered drug X, then patients will experience reduced fatigue from cancer treatment. A hypothesis can adopt when X/then Y format when it primarily aims to expose a connection between two variables
Hypothesis Examples
Here are some research hypothesis examples: If you leave the lights on, then it takes longer for people to fall asleep. If you refrigerate apples, they last longer before going bad. If you keep the curtains closed, then you need less electricity to heat or cool the house (the electric bill is lower). If you leave a bucket of water uncovered ...
Subject Guides: Scientific Method: Step 3: HYPOTHESIS
The hypothesis is often written using the words "IF" and "THEN." For example, "If I do not study, then I will fail the test." The "if' and "then" statements reflect your independent and dependent variables. The hypothesis should relate back to your original question and must be testable.
How to Write a Strong Hypothesis
Step 5: Phrase your hypothesis in three ways. To identify the variables, you can write a simple prediction in if … then form. The first part of the sentence states the independent variable and the second part states the dependent variable. If a first-year student starts attending more lectures, then their exam scores will improve.
How to Write a Hypothesis [31 Tips
Tip 11: Review Existing Literature. Previous research offers insights into forming a hypothesis. Conduct a thorough literature review to identify trends and gaps. Use these studies to refine and build upon your hypothesis. Examples: Studies showing a link between screen time and anxiety.
How to Write a Hypothesis w/ Strong Examples
Associative Hypothesis Examples. There is an association between the number of hours spent on social media and the level of anxiety in teenagers. Daily consumption of green tea is associated with weight loss in adults. The frequency of public transport use correlates with the level of urban air pollution.
How to Write a Hypothesis
Define a research question. The first step in formulating a hypothesis is to brainstorm a research question. Use your writing skills to write a research question that's specific, clear, focused, and manageable. Make sure you have the resources to conduct whatever experiment you'll need to answer the question.
Research Hypothesis: Definition, Types, Examples and Quick Tips
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.
What Is a Hypothesis? The Scientific Method
In science, a hypothesis is part of the scientific method. It is a prediction or explanation that is tested by an experiment. Observations and experiments may disprove a scientific hypothesis, but can never entirely prove one. In the study of logic, a hypothesis is an if-then proposition, typically written in the form, "If X, then Y."
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Many researchers use this hypothesis to explore the relationship between variables rather than the groups. Non-directional; You can take a guess from the name. This type of H1 does not provide a specific prediction for the research outcome. Here are some examples for your better understanding of how to write a hypothesis.
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Merriam Webster defines a hypothesis as "an assumption or concession made for the sake of argument.". In other words, a hypothesis is an educated guess. Scientists make a reasonable assumption--or a hypothesis--then design an experiment to test whether it's true or not.
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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.
What Are Effective Hypothesis Examples?
Hypotheses Examples: If, Then. If you get at least 6 hours of sleep, you will do better on tests than if you get less sleep. If you drop a ball, it will fall toward the ground. If you drink coffee before going to bed, then it will take longer to fall asleep. If you cover a wound with a bandage, then it will heal with less scarring.
5.2
5.2 - Writing Hypotheses. The first step in conducting a hypothesis test is to write the hypothesis statements that are going to be tested. For each test you will have a null hypothesis (H 0) and an alternative hypothesis (H a). When writing hypotheses there are three things that we need to know: (1) the parameter that we are testing (2) the ...
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Conditional statements, framed as 'if-then' constructs, are essential in mathematics for delineating logical relationships between ideas. ... a hypothesis (the 'if' part) and a conclusion (the 'then' part). Written symbolically, it takes the form: ... Write the converse, inverse, and contrapositive for the statement: "If a bird is a ...
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A hypothesis is a clear, testable statement. It includes a forecast or prediction based on the assumption. Unlike an idea or open question, which are generally vague or speculative, a hypothesis is a precise, verifiable proposition that outlines both the action and expected outcome.There are several different formats that Scrum Teams can use to write a hypothesis, including:
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Guide to IF THEN Statement in SQL: Learn How It Works
The IF THEN statement is part of the control statements in SQL. Simply put, it helps in decision-making and directs program control flow. The IF statement associates a condition, and then a sequence of statements follows. If the condition is evaluated as accurate, the statements enclosed within the keywords THEN and END IF get executed.

Research Question	Is the population mean different from \( \mu_{0} \)?	Is the population mean greater than \(\mu_{0}\)?	Is the population mean less than \(\mu_{0}\)?
Null Hypothesis, \(H_{0}\)	\(\mu=\mu_{0} \)	\(\mu=\mu_{0} \)	\(\mu=\mu_{0} \)
Alternative Hypothesis, \(H_{a}\)	\(\mu\neq \mu_{0} \)	\(\mu> \mu_{0} \)	\(\mu<\mu_{0} \)
Type of Hypothesis Test	Two-tailed, non-directional	Right-tailed, directional	Left-tailed, directional

Research Question	Is the population proportion different from \(p_0\)?	Is the population proportion greater than \(p_0\)?	Is the population proportion less than \(p_0\)?
Null Hypothesis, \(H_{0}\)	\(p=p_0\)	\(p= p_0\)	\(p= p_0\)
Alternative Hypothesis, \(H_{a}\)	\(p\neq p_0\)	\(p> p_0\)	\(p< p_0\)
Type of Hypothesis Test	Two-tailed, non-directional	Right-tailed, directional	Left-tailed, directional

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Table of contents

Variables in hypotheses

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Step 2: Do some preliminary research

Step 3: Formulate your hypothesis

Step 4: Refine your hypothesis

Step 5: Phrase your hypothesis in three ways

Step 6. Write a null hypothesis

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How to Write a Hypothesis [31 Tips + Examples]

Writing a Hypothesis: The Basics

31 Tips for Writing a Hypothesis

Tip 1: Start with a Clear Research Question

Tip 2: Do Background Research

Tip 3: Identify Independent and Dependent Variables

Tip 4: Make Your Hypothesis Testable

Tip 5: Be Specific and Concise

Tip 6: Choose Simple Language

Tip 7: Formulate a Null Hypothesis

Tip 8: State Alternative Hypotheses

Tip 9: Use “If…Then” Statements

Tip 10: Avoid Assumptions

Tip 11: Review Existing Literature

Tip 12: Consider Multiple Variables

Tip 13: Review Ethical Considerations

Tip 14: Test with Pilot Studies

Tip 15: Build Hypotheses on Existing Theories

Tip 16: Address Real-World Problems

Tip 17: Aim for Clear, Measurable Outcomes

Tip 18: Stay Open to Unexpected Results

Tip 19: Keep Hypotheses Relevant

Tip 20: Collaborate with Peers

Tip 21: Re-evaluate Hypotheses Periodically

Tip 22: Develop Compelling Visuals

Tip 23: Refine Your Data Collection Plan

Tip 24: Focus on Logical Progression

Tip 25: Test Against Diverse Samples

Tip 26: Use Control Groups