hypothesis with if then because

Hypothesis If Then

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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Writing a hypothesis using if and then

Anne Helmenstine, Ph.D. is an author and consultant with a broad scientific and medical background. Read more

Updated August 19, 2015.

Question: What Are Examples of a Hypothesis?

Answer: Although you could state a scientific hypothesis in various ways, most hypothesis are either "If, then" statements or else forms of the null hypothesis. The null hypothesis sometimes is called the "no difference" hypothesis. The null hypothesis is good for experimentation because it’;s simple to disprove.

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If you disprove a null hypothesis. that is evidence for a relationship between the variables you are examining. For example:

Examples of the Null Hypothesis

• Hyperactivity is unrelated to eating sugar.
• All daisies have the same number of petals.
• 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.

Examples of an If, Then Hypothesis

• 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

While there are many ways to state a hypothesis, you may wish to revise your first hypothesis in order to make it easier to design an experiment to test it. 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 a hypothesis:

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, for the next week you’;ll avoid greasy food and see what happens. Now, this is not a very 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 which 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 easy 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 breakout 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.

A hypothesis is a description of a pattern in nature or an explanation about some real-world phenomenon that can be tested through observation and experimentation. The most common way a hypothesis is used in scientific research is as a tentative, testable, and falsifiable statement that explains some observed phenomenon in nature.ok ok [1] We more specifically call this kind of statement an explanatory hypothesis . However, a hypothesis can also be a statement that describes an observed pattern in nature. In this case we call the statement a generalizing hypothesis . [2] [3] Hypotheses can generate predictions . statements that propose that one variable will drive some effect on or change in another variable in the result of a controlled experiment. However, many science resources promote the myth that a hypothesis is simply an educated guess and no different from a prediction. [4] More on this misunderstanding below.

Many academic fields, from the physical sciences to the life sciences to the social sciences, use hypothesis testing as a means of testing ideas to learn about the world and advance scientific knowledge. Whether you are a beginning scholar or a beginning student taking a class in a science subject, understanding what hypotheses are and being able to generate hypotheses and predictions yourself is very important. These instructions will help get you started.

Part One of Two: Preparing to Write a Hypothesis Edit

Select a topic. Pick a topic that interests you, and that you think it would be good to know more about.

• If you are writing a hypothesis for a school assignment, this step may be taken care of for you.

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Read existing research. Gather all the information you can about the topic you’ve selected. You’ll need to become an expert on the subject and develop a good grasp of what is already known about the topic.

• Focus on academic and scholarly writing. You need to be certain that your information is unbiased, accurate, and comprehensive.
• You can find information in textbooks, at a library, and online. If you are in school, you can also ask for help from teachers, librarians, and your peers.

Analyze the literature. Spend some time reading the materials you’ve collected. As you do so, look for and make note of unanswered questions in the literature. These can provide excellent ideas for areas to investigate.

• For example, if you are interested in the effects of caffeine on the human body, but notice that nobody seems to have explored whether caffeine affects men differently than it does women, this could be something to formulate a hypothesis about. Or, if you are interested in organic farming, you might notice that no one has tested whether organic fertilizer results in different growth rates for plants than non-organic fertilizer.
• You can sometimes find holes in the existing literature by looking for statements like “it is unknown” or places where information is clearly missing. You might also find a claim in the literature that seems far-fetched, unlikely, or too good to be true, like that caffeine improves math skills. If the claim is testable, you could provide a great service to scientific knowledge by doing your own investigation. If you confirm the claim, the claim becomes even more credible. If you do not find support for the claim, you are helping with the necessary self-correcting aspect of science.
• Examining these types of questions provides an excellent way for you to set yourself apart by filling in important gaps in a field of study.

Generate questions. After studying the literature on your topic, generate one or more unanswered questions you’d be interested in exploring further. These are your research questions.

• Following the examples above, you might ask: “How does caffeine affect women as compared to men?” or “How does organic fertilizer affect plant growth compared to non-organic fertilizer?” The rest of your research will be aimed at answering these questions.

Look for clues as to what the answer might be. Once you have generated your research question or questions, look in the literature to see if the existing findings and/or theories about the topic provide any clues that would allow you to come up with ideas about what the answers to your research questions might be. If so, these clues can form the basis for your hypothesis.

• Following the examples above, if you discover in the literature that there is a pattern that some other types of stimulants seem to affect women more than men, this could be a clue that the same pattern might be true for caffeine. Similarly, if you observe the pattern that organic fertilizer seems to be associated with smaller plants overall, you might explain this pattern with the hypothesis that plants exposed to organic fertilizer grow more slowly than plants exposed to non-organic fertilizer.

Determine your variables. A generalizing hypothesis describes a pattern you think may exist between two variables: an independent variable and a dependent variable. If your experiments confirm the pattern, you may decide to suggest a reason that the pattern exists or a mechanism that generates the pattern. The reason or mechanism you suggest is an explanatory hypothesis .

• You can think of the independent variable as the one that is causing some kind of difference or effect to occur. In the examples, the independent variable would be gender, i.e. whether a person is male or female, and fertilizer type, i.e. whether the fertilizer is organic or non-organically-based.
• The dependent variable is what is affected by (i.e. “depends” on) the independent variable. In the examples above, the dependent variable would be the measured impact of caffeine or fertilizer.
• Your hypothesis should only suggest one relationship. Most importantly, it should only have one independent variable. If you have more than one, you won’t be able to determine which one is actually the source of any effects you might observe.

Generate a simple hypothesis. Once you’ve spent some time thinking about your research question and variables, write down your initial idea about how the variables might be related as a simple declarative statement.

• Don’t worry too much at this point about being precise or detailed.
• In the examples above, one hypothesis would make a statement about whether a person’s gender might impact the way the person is affected by caffeine; for example, at this point, your hypothesis might simply be: “a person’s gender is related to how caffeine affects his or her heart rate.” The other hypothesis would make a general statement about plant growth and fertilizer; for example your simple explanatory hypothesis might be “plants given different types of fertilizer are different sizes because they grow at different rates.”

Decide on direction. Hypotheses can either be directional or non-directional. A non-directional hypothesis simply says that one variable affects the other in some way, but does not say specifically in what way. A directional hypothesis provides more information about the nature (or “direction”) of the relationship, stating specifically how one variable affects the other.

• Using our example, our non-directional hypotheses would be “there is a relationship between a person’s gender and how much caffeine increases the person’s heart rate,” and “there is a relationship between fertilizer type and the speed at which plants grow.”
• Directional predictions using the same example hypotheses above would be. “Women will experience a greater increase in heart rate after consuming caffeine than will men,” and “plants fertilized with non-organic fertilizer will grow faster than those fertilized with organic fertilizer.” Indeed, these predictions and the hypotheses that allow for them are very different kinds of statements. More on this distinction below.
• If the literature provides any basis for making a directional prediction, it is better to do so, because it provides more information. Especially in the physical sciences, non-directional predictions are often seen as inadequate.

Get specific. Once you have an initial idea on paper, it’s time to start refining. Make your hypotheses as specific as you can, so it’s clear exactly what ideas you will be testing and make your predictions specific and measurable so that they provide evidence of a relationship between the variables.

• Where necessary, specify the population (i.e. the people or things) about which you hope to uncover new knowledge. For example, if you were only interested the effects of caffeine on elderly people, your prediction might read: “Women over the age of 65 will experience a greater increase in heart rate than will men of the same age.” If you were interested only in how fertilizer affects tomato plants, your prediction might read: “Tomato plants treated with non-organic fertilizer will grow faster in the first three months than will tomato plants treated with organic fertilizer.”

Make sure it is testable. Your hypothesis must suggest a relationship between two variables or a reason that two variables are related that can feasibly be observed and measured in the real and observable world .

• For example, you would not want to make the hypothesis: “red is the prettiest color.” This statement is an opinion and it cannot be tested with an experiment. However, proposing the generalizing hypothesis that red is the most popular color is testable with a simple random survey. If you do indeed confirm that red is the most popular color, your next step may be to ask: Why is red the most popular color? The answer you propose is your explanatory hypothesis .
• Often, hypotheses are stated in the form of if-then sentences. For example, “if children are given caffeine, then their heart rates will increase.” This statement is not a hypothesis. This kind of statement is a brief description of an experimental method followed by a prediction and is the most common way that hypotheses are misrepresented in science education. An easy way to get to the hypothesis for this method and prediction is to ask yourself why you think heart rates will increase if children are given caffeine. Your explanatory hypothesis in this case may be that caffeine is a stimulant. At this point, some scientists write what is called a research hypothesis . a statement that includes the hypothesis, the experiment, and the prediction all in one statement: If caffeine is a stimulant, and some children are given a drink with caffeine while others are given a drink without caffeine, then the heart rates of those children given a caffeinated drink will increase more than the heart rate of children given a non-caffeinated drink.
• It may sound strange, but researchers rarely ever prove that a hypothesis is right or wrong. Instead, they look for evidence that the opposite of their hypotheses is probably not true. If the opposite (caffeine is not a stimulant) is probably not true, the hypothesis (caffeine is a stimulant) probably is true.
• Using the above example, if you were to test the effects of caffeine on the heart rates of children, evidence that your hypothesis is not true, sometimes called the null hypothesis . could occur if the heart rates of both the children given the caffeinated drink and the children given the non-caffeinated drink (called the placebo control) did not change, or lowered or raised with the same magnitude, if there was no difference between the two groups of children. If you wanted to test the effects of different fertilizer types, evidence that your hypothesis was not true would be that the plants grew at the same rate, regardless of fertilizer, or if plants treated with organic fertilizer grew faster. It is important to note here that the null hypothesis actually becomes much more useful when researchers test the significance of their results with statistics. When statistics are used on the results of an experiment, a researcher is testing the idea of the null statistical hypothesis. For example, that there is no relationship between two variables or that there is no difference between two groups. [5]

Test your hypothesis. Make your observations or conduct your experiment. Your evidence may allow you to reject your null hypotheses, thus lending support to your experimental hypothesis. However, your evidence may not allow you to reject your null hypothesis and this is okay. Any result is important, even when your result sends you back to the drawing board. Constantly having to go “back to the drawing board” and refine your ideas is how authentic science really works! [6]

When examining the literature, look for research that is similar to what you want to do, and try to build on the findings of other researchers. But also look for claims that you think are suspicious, and test them yourself.

Be specific in your hypotheses, but not so specific that your hypothesis can’t be applied to anything outside your specific experiment. You definitely want to be clear about the population about which you are interested in drawing conclusions, but nobody (except your roommates) will be interested in reading a paper with the prediction: “my three roommates will each be able to do a different amount of pushups.”

Keep your feelings and opinions out of your research. Hypotheses should never say “I believe. ” “I think. ” “I feel. ” or “My opinion is that. “

Remember that science is not necessarily a linear process and can be approached in various ways. [7]

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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: Jan 26, 2024 10:39 AM
• URL: https://harford.libguides.com/scientific_method

What is a scientific hypothesis?

It's the initial building block in the scientific method.

Hypothesis basics

What makes a hypothesis testable.

• Types of hypotheses
• Hypothesis versus theory

Additional resources

Bibliography.

A scientific hypothesis is a tentative, testable explanation for a phenomenon in the natural world. It's the initial building block in the scientific method . Many describe it as an "educated guess" based on prior knowledge and observation. While this is true, a hypothesis is more informed than a guess. While an "educated guess" suggests a random prediction based on a person's expertise, developing a hypothesis requires active observation and background research. 

The basic idea of a hypothesis is that there is no predetermined outcome. For a solution to be termed a scientific hypothesis, it has to be an idea that can be supported or refuted through carefully crafted experimentation or observation. This concept, called falsifiability and testability, was advanced in the mid-20th century by Austrian-British philosopher Karl Popper in his famous book "The Logic of Scientific Discovery" (Routledge, 1959).

A key function of a hypothesis is to derive predictions about the results of future experiments and then perform those experiments to see whether they support the predictions.

A hypothesis is usually written in the form of an if-then statement, which gives a possibility (if) and explains what may happen because of the possibility (then). The statement could also include "may," according to California State University, Bakersfield .

Here are some examples of hypothesis statements:

• If garlic repels fleas, then a dog that is given garlic every day will not get fleas.
• If sugar causes cavities, then people who eat a lot of candy may be more prone to cavities.
• If ultraviolet light can damage the eyes, then maybe this light can cause blindness.

A useful hypothesis should be testable and falsifiable. That means that it should be possible to prove it wrong. A theory that can't be proved wrong is nonscientific, according to Karl Popper's 1963 book " Conjectures and Refutations ."

An example of an untestable statement is, "Dogs are better than cats." That's because the definition of "better" is vague and subjective. However, an untestable statement can be reworded to make it testable. For example, the previous statement could be changed to this: "Owning a dog is associated with higher levels of physical fitness than owning a cat." With this statement, the researcher can take measures of physical fitness from dog and cat owners and compare the two.

Types of scientific hypotheses

In an experiment, researchers generally state their hypotheses in two ways. The null hypothesis predicts that there will be no relationship between the variables tested, or no difference between the experimental groups. The alternative hypothesis predicts the opposite: that there will be a difference between the experimental groups. This is usually the hypothesis scientists are most interested in, according to the University of Miami .

For example, a null hypothesis might state, "There will be no difference in the rate of muscle growth between people who take a protein supplement and people who don't." The alternative hypothesis would state, "There will be a difference in the rate of muscle growth between people who take a protein supplement and people who don't."

If the results of the experiment show a relationship between the variables, then the null hypothesis has been rejected in favor of the alternative hypothesis, according to the book " Research Methods in Psychology " (​​BCcampus, 2015). 

There are other ways to describe an alternative hypothesis. The alternative hypothesis above does not specify a direction of the effect, only that there will be a difference between the two groups. That type of prediction is called a two-tailed hypothesis. If a hypothesis specifies a certain direction — for example, that people who take a protein supplement will gain more muscle than people who don't — it is called a one-tailed hypothesis, according to William M. K. Trochim , a professor of Policy Analysis and Management at Cornell University.

Sometimes, errors take place during an experiment. These errors can happen in one of two ways. A type I error is when the null hypothesis is rejected when it is true. This is also known as a false positive. A type II error occurs when the null hypothesis is not rejected when it is false. This is also known as a false negative, according to the University of California, Berkeley . 

A hypothesis can be rejected or modified, but it can never be proved correct 100% of the time. For example, a scientist can form a hypothesis stating that if a certain type of tomato has a gene for red pigment, that type of tomato will be red. During research, the scientist then finds that each tomato of this type is red. Though the findings confirm the hypothesis, there may be a tomato of that type somewhere in the world that isn't red. Thus, the hypothesis is true, but it may not be true 100% of the time.

Scientific theory vs. scientific hypothesis

The best hypotheses are simple. They deal with a relatively narrow set of phenomena. But theories are broader; they generally combine multiple hypotheses into a general explanation for a wide range of phenomena, according to the University of California, Berkeley . For example, a hypothesis might state, "If animals adapt to suit their environments, then birds that live on islands with lots of seeds to eat will have differently shaped beaks than birds that live on islands with lots of insects to eat." After testing many hypotheses like these, Charles Darwin formulated an overarching theory: the theory of evolution by natural selection.

"Theories are the ways that we make sense of what we observe in the natural world," Tanner said. "Theories are structures of ideas that explain and interpret facts." 

• Read more about writing a hypothesis, from the American Medical Writers Association.
• Find out why a hypothesis isn't always necessary in science, from The American Biology Teacher.
• Learn about null and alternative hypotheses, from Prof. Essa on YouTube .

Encyclopedia Britannica. Scientific Hypothesis. Jan. 13, 2022. https://www.britannica.com/science/scientific-hypothesis

Karl Popper, "The Logic of Scientific Discovery," Routledge, 1959.

California State University, Bakersfield, "Formatting a testable hypothesis." https://www.csub.edu/~ddodenhoff/Bio100/Bio100sp04/formattingahypothesis.htm  

Karl Popper, "Conjectures and Refutations," Routledge, 1963.

Price, P., Jhangiani, R., & Chiang, I., "Research Methods of Psychology — 2nd Canadian Edition," BCcampus, 2015.‌

University of Miami, "The Scientific Method" http://www.bio.miami.edu/dana/161/evolution/161app1_scimethod.pdf  

William M.K. Trochim, "Research Methods Knowledge Base," https://conjointly.com/kb/hypotheses-explained/  

University of California, Berkeley, "Multiple Hypothesis Testing and False Discovery Rate" https://www.stat.berkeley.edu/~hhuang/STAT141/Lecture-FDR.pdf  

University of California, Berkeley, "Science at multiple levels" https://undsci.berkeley.edu/article/0_0_0/howscienceworks_19

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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

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Sat / act prep online guides and tips, 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

Ashley Sufflé Robinson has a Ph.D. in 19th Century English Literature. As a content writer for PrepScholar, Ashley is passionate about giving college-bound students the in-depth information they need to get into the school of their dreams.

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2.11: If Then Statements

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Hypothesis followed by a conclusion in a conditional statement.

Conditional Statements

A conditional statement (also called an if-then statement ) is a statement with a hypothesis followed by a conclusion . The hypothesis is the first, or “if,” part of a conditional statement. The conclusion is the second, or “then,” part of a conditional statement. The conclusion is the result of a hypothesis.

If-then statements might not always be written in the “if-then” form. Here are some examples of conditional statements:

• Statement 1: If you work overtime, then you’ll be paid time-and-a-half.
• Statement 2: I’ll wash the car if the weather is nice.
• Statement 3: If 2 divides evenly into \(x\), then \(x\) is an even number.
• Statement 4: I’ll be a millionaire when I win the lottery.
• Statement 5: All equiangular triangles are equilateral.

Statements 1 and 3 are written in the “if-then” form. The hypothesis of Statement 1 is “you work overtime.” The conclusion is “you’ll be paid time-and-a-half.” Statement 2 has the hypothesis after the conclusion. If the word “if” is in the middle of the statement, then the hypothesis is after it. The statement can be rewritten: If the weather is nice, then I will wash the car. Statement 4 uses the word “when” instead of “if” and is like Statement 2. It can be written: If I win the lottery, then I will be a millionaire. Statement 5 “if” and “then” are not there. It can be rewritten: If a triangle is equiangular, then it is equilateral.

What if you were given a statement like "All squares are rectangles"? How could you determine the hypothesis and conclusion of this statement?

Example \(\PageIndex{1}\)

Determine the hypothesis and conclusion: I'll bring an umbrella if it rains.

Hypothesis: "It rains." Conclusion: "I'll bring an umbrella."

Example \(\PageIndex{2}\)

Determine the hypothesis and conclusion: All right angles are \(90^{\circ}\).

Hypothesis: "An angle is right." Conclusion: "It is \(90^{\circ}\)."

Example \(\PageIndex{3}\)

Use the statement: I will graduate when I pass Calculus.

Rewrite in if-then form and determine the hypothesis and conclusion.

This statement can be rewritten as If I pass Calculus, then I will graduate. The hypothesis is “I pass Calculus,” and the conclusion is “I will graduate.”

Example \(\PageIndex{4}\)

Use the statement: All prime numbers are odd.

Rewrite in if-then form, determine the hypothesis and conclusion, and determine whether this is a true statement.

This statement can be rewritten as If a number is prime, then it is odd. The hypothesis is "a number is prime" and the conclusion is "it is odd". This is not a true statement (remember that not all conditional statements will be true!) since 2 is a prime number but it is not odd.

Example \(\PageIndex{5}\)

Determine the hypothesis and conclusion: Sarah will go to the store if Riley does the laundry.

The statement can be rewritten as "If Riley does the laundry then Sarah will go to the store." The hypothesis is "Riley does the laundry" and the conclusion is "Sarah will go to the store."

Determine the hypothesis and the conclusion for each statement.

• If 5 divides evenly into \(x\), then \(x\) ends in 0 or 5.
• If a triangle has three congruent sides, it is an equilateral triangle.
• Three points are coplanar if they all lie in the same plane.
• If \(x=3\), then \(x^2=9\).
• If you take yoga, then you are relaxed.
• All baseball players wear hats.
• I'll learn how to drive when I am 16 years old.
• If you do your homework, then you can watch TV.
• Alternate interior angles are congruent if lines are parallel.
• All kids like ice cream.

Additional Resources

Video: If-Then Statements Principles - Basic

Activities: If-Then Statements Discussion Questions

Study Aids: Conditional Statements Study Guide

Practice: If Then Statements

Real World: If Then Statements

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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 6 months ago (category: Articles )

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How to Write a Great Hypothesis

Hypothesis Format, Examples, and Tips

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Amy Morin, LCSW, is a psychotherapist and international bestselling author. Her books, including "13 Things Mentally Strong People Don't Do," have been translated into more than 40 languages. Her TEDx talk,  "The Secret of Becoming Mentally Strong," is one of the most viewed talks of all time.

Verywell / Alex Dos Diaz

• The Scientific Method

Hypothesis Format

Falsifiability of a hypothesis, operational definitions, types of hypotheses, hypotheses examples.

• Collecting Data

Frequently Asked Questions

A hypothesis is a tentative statement about the relationship between two or more  variables. It is a specific, testable prediction about what you expect to happen in a study.

One hypothesis example would be a study designed to look at the relationship between sleep deprivation and test performance might have a hypothesis that states: "This study is designed to assess the hypothesis that sleep-deprived people will perform worse on a test than individuals who are not sleep-deprived."

This article explores how a hypothesis is used in psychology research, how to write a good hypothesis, and the different types of hypotheses you might use.

The Hypothesis in the Scientific Method

In the scientific method , whether it involves research in psychology, biology, or some other area, a hypothesis represents what the researchers think will happen in an experiment. The scientific method involves the following steps:

• Forming a question
• Performing background research
• Creating a hypothesis
• Designing an experiment
• Collecting data
• Analyzing the results
• Drawing conclusions
• Communicating the results

The hypothesis is a prediction, but it involves more than a guess. Most of the time, the hypothesis begins with a question which is then explored through background research. It is only at this point that researchers begin to develop a testable hypothesis. Unless you are creating an exploratory study, your hypothesis should always explain what you  expect  to happen.

In a study exploring the effects of a particular drug, the hypothesis might be that researchers expect the drug to have some type of effect on the symptoms of a specific illness. In psychology, the hypothesis might focus on how a certain aspect of the environment might influence a particular behavior.

Remember, a hypothesis does not have to be correct. While the hypothesis predicts what the researchers expect to see, the goal of the research is to determine whether this guess is right or wrong. When conducting an experiment, researchers might explore a number of factors to determine which ones might contribute to the ultimate outcome.

In many cases, researchers may find that the results of an experiment  do not  support the original hypothesis. When writing up these results, the researchers might suggest other options that should be explored in future studies.

In many cases, researchers might draw a hypothesis from a specific theory or build on previous research. For example, prior research has shown that stress can impact the immune system. So a researcher might hypothesize: "People with high-stress levels will be more likely to contract a common cold after being exposed to the virus than people who have low-stress levels."

In other instances, researchers might look at commonly held beliefs or folk wisdom. "Birds of a feather flock together" is one example of folk wisdom that a psychologist might try to investigate. The researcher might pose a specific hypothesis that "People tend to select romantic partners who are similar to them in interests and educational level."

Elements of a Good Hypothesis

So how do you write a good hypothesis? When trying to come up with a hypothesis for your research or experiments, ask yourself the following questions:

• Is your hypothesis based on your research on a topic?
• Can your hypothesis be tested?
• Does your hypothesis include independent and dependent variables?

Before you come up with a specific hypothesis, spend some time doing background research. Once you have completed a literature review, start thinking about potential questions you still have. Pay attention to the discussion section in the  journal articles you read . Many authors will suggest questions that still need to be explored.

To form a hypothesis, you should take these steps:

• Collect as many observations about a topic or problem as you can.
• Evaluate these observations and look for possible causes of the problem.
• Create a list of possible explanations that you might want to explore.
• After you have developed some possible hypotheses, think of ways that you could confirm or disprove each hypothesis through experimentation. This is known as falsifiability.

In the scientific method ,  falsifiability is an important part of any valid hypothesis.   In order to test a claim scientifically, it must be possible that the claim could be proven false.

Students sometimes confuse the idea of falsifiability with the idea that it means that something is false, which is not the case. What falsifiability means is that  if  something was false, then it is possible to demonstrate that it is false.

One of the hallmarks of pseudoscience is that it makes claims that cannot be refuted or proven false.

A variable is a factor or element that can be changed and manipulated in ways that are observable and measurable. However, the researcher must also define how the variable will be manipulated and measured in the study.

For example, a researcher might operationally define the variable " test anxiety " as the results of a self-report measure of anxiety experienced during an exam. A "study habits" variable might be defined by the amount of studying that actually occurs as measured by time.

These precise descriptions are important because many things can be measured in a number of different ways. One of the basic principles of any type of scientific research is that the results must be replicable.   By clearly detailing the specifics of how the variables were measured and manipulated, other researchers can better understand the results and repeat the study if needed.

Some variables are more difficult than others to define. How would you operationally define a variable such as aggression ? For obvious ethical reasons, researchers cannot create a situation in which a person behaves aggressively toward others.

In order to measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming other people. In this situation, the researcher might utilize a simulated task to measure aggressiveness.

Hypothesis Checklist

• Does your hypothesis focus on something that you can actually test?
• Does your hypothesis include both an independent and dependent variable?
• Can you manipulate the variables?
• Can your hypothesis be tested without violating ethical standards?

The hypothesis you use will depend on what you are investigating and hoping to find. Some of the main types of hypotheses that you might use include:

• Simple hypothesis : This type of hypothesis suggests that there is a relationship between one independent variable and one dependent variable.
• Complex hypothesis : This type of hypothesis suggests a relationship between three or more variables, such as two independent variables and a dependent variable.
• Null hypothesis : This hypothesis suggests no relationship exists between two or more variables.
• Alternative hypothesis : This hypothesis states the opposite of the null hypothesis.
• Statistical hypothesis : This hypothesis uses statistical analysis to evaluate a representative sample of the population and then generalizes the findings to the larger group.
• Logical hypothesis : This hypothesis assumes a relationship between variables without collecting data or evidence.

A hypothesis often follows a basic format of "If {this happens} then {this will happen}." One way to structure your hypothesis is to describe what will happen to the  dependent variable  if you change the  independent variable .

The basic format might be: "If {these changes are made to a certain independent variable}, then we will observe {a change in a specific dependent variable}."

A few examples of simple hypotheses:

• "Students who eat breakfast will perform better on a math exam than students who do not eat breakfast."
• Complex hypothesis: "Students who experience test anxiety before an English exam will get lower scores than students who do not experience test anxiety."​
• "Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone."

Examples of a complex hypothesis include:

• "People with high-sugar diets and sedentary activity levels are more likely to develop depression."
• "Younger people who are regularly exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces."

Examples of a null hypothesis include:

• "Children who receive a new reading intervention will have scores different than students who do not receive the intervention."
• "There will be no difference in scores on a memory recall task between children and adults."

Examples of an alternative hypothesis:

• "Children who receive a new reading intervention will perform better than students who did not receive the intervention."
• "Adults will perform better on a memory task than children." 

Collecting Data on Your Hypothesis

Once a researcher has formed a testable hypothesis, the next step is to select a research design and start collecting data. The research method depends largely on exactly what they are studying. There are two basic types of research methods: descriptive research and experimental research.

Descriptive Research Methods

Descriptive research such as  case studies ,  naturalistic observations , and surveys are often used when it would be impossible or difficult to  conduct an experiment . These methods are best used to describe different aspects of a behavior or psychological phenomenon.

Once a researcher has collected data using descriptive methods, a correlational study can then be used to look at how the variables are related. This type of research method might be used to investigate a hypothesis that is difficult to test experimentally.

Experimental Research Methods

Experimental methods  are used to demonstrate causal relationships between variables. In an experiment, the researcher systematically manipulates a variable of interest (known as the independent variable) and measures the effect on another variable (known as the dependent variable).

Unlike correlational studies, which can only be used to determine if there is a relationship between two variables, experimental methods can be used to determine the actual nature of the relationship—whether changes in one variable actually  cause  another to change.

A Word From Verywell

The hypothesis is a critical part of any scientific exploration. It represents what researchers expect to find in a study or experiment. In situations where the hypothesis is unsupported by the research, the research still has value. Such research helps us better understand how different aspects of the natural world relate to one another. It also helps us develop new hypotheses that can then be tested in the future.

Some examples of how to write a hypothesis include:

• "Staying up late will lead to worse test performance the next day."
• "People who consume one apple each day will visit the doctor fewer times each year."
• "Breaking study sessions up into three 20-minute sessions will lead to better test results than a single 60-minute study session."

The four parts of a hypothesis are:

• The research question
• The independent variable (IV)
• The dependent variable (DV)
• The proposed relationship between the IV and DV

Castillo M. The scientific method: a need for something better? . AJNR Am J Neuroradiol. 2013;34(9):1669-71. doi:10.3174/ajnr.A3401

Nevid J. Psychology: Concepts and Applications. Wadworth, 2013.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

What Is a Hypothesis? (Science)

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• Ph.D., Biomedical Sciences, University of Tennessee at Knoxville
• B.A., Physics and Mathematics, Hastings College

A hypothesis (plural hypotheses) is a proposed explanation for an observation. The definition depends on the subject.

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 ."

In common usage, a hypothesis is simply a proposed explanation or prediction, which may or may not be tested.

Writing a Hypothesis

Most scientific hypotheses are proposed in the if-then format because it's easy to design an experiment to see whether or not a cause and effect relationship exists between the independent variable and the dependent variable . The hypothesis is written as a prediction of the outcome of the experiment.

• Null Hypothesis and Alternative Hypothesis

Statistically, it's easier to show there is no relationship between two variables than to support their connection. So, scientists often propose the null hypothesis . The null hypothesis assumes changing the independent variable will have no effect on the dependent variable.

In contrast, the alternative hypothesis suggests changing the independent variable will have an effect on the dependent variable. Designing an experiment to test this hypothesis can be trickier because there are many ways to state an alternative hypothesis.

For example, consider a possible relationship between getting a good night's sleep and getting good grades. The null hypothesis might be stated: "The number of hours of sleep students get is unrelated to their grades" or "There is no correlation between hours of sleep and grades."

An experiment to test this hypothesis might involve collecting data, recording average hours of sleep for each student and grades. If a student who gets eight hours of sleep generally does better than students who get four hours of sleep or 10 hours of sleep, the hypothesis might be rejected.

But the alternative hypothesis is harder to propose and test. The most general statement would be: "The amount of sleep students get affects their grades." The hypothesis might also be stated as "If you get more sleep, your grades will improve" or "Students who get nine hours of sleep have better grades than those who get more or less sleep."

In an experiment, you can collect the same data, but the statistical analysis is less likely to give you a high confidence limit.

Usually, a scientist starts out with the null hypothesis. From there, it may be possible to propose and test an alternative hypothesis, to narrow down the relationship between the variables.

Example of a Hypothesis

Examples of a hypothesis include:

• If you drop a rock and a feather, (then) they will fall at the same rate.
• Plants need sunlight in order to live. (if sunlight, then life)
• Eating sugar gives you energy. (if sugar, then energy)
• White, Jay D.  Research in Public Administration . Conn., 1998.
• Schick, Theodore, and Lewis Vaughn.  How to Think about Weird Things: Critical Thinking for a New Age . McGraw-Hill Higher Education, 2002.
• Null Hypothesis Definition and Examples
• Definition of a Hypothesis
• What Are the Elements of a Good Hypothesis?
• Six Steps of the Scientific Method
• What Are Examples of a Hypothesis?
• Understanding Simple vs Controlled Experiments
• Scientific Method Flow Chart
• Scientific Method Vocabulary Terms
• What Is a Testable Hypothesis?
• Null Hypothesis Examples
• What 'Fail to Reject' Means in a Hypothesis Test
• How To Design a Science Fair Experiment
• What Is an Experiment? Definition and Design
• Hypothesis Test for the Difference of Two Population Proportions
• How to Conduct a Hypothesis Test

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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.

Table of contents

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

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

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

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

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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 ).

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

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

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

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

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

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

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

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

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

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

Methodology

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

Research bias

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

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

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

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

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

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Hypothesis Maker Online

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

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

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

👍 What Does a Good Hypothesis Mean?

• 🧭 Steps to Making a Good Hypothesis

🔗 References

📄 hypothesis maker: how to use it.

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

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

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

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

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

⚗️ What Is a Hypothesis in the Scientific Method?

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

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

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

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

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

Hypothesis vs. Theory

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

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

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

You should observe the stated assumption to prove its accuracy.

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

This general principle can apply to many specific cases.

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

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

🧭 6 Steps to Making a Good Hypothesis

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

Step #1: Ask Questions

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

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

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

Step #2: Do Initial Research

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

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

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

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

Step #3: Identify Your Variables

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

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

Step #4: Formulate Your Hypothesis

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

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

Step #5: Gather Relevant Data

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

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

Step #6: Record Your Findings

Finally, write down your conclusions in a research paper .

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

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

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

❓ Hypothesis Formulator FAQ

Updated: Oct 25th, 2023

• How to Write a Hypothesis in 6 Steps - Grammarly
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Use our hypothesis maker whenever you need to formulate a hypothesis for your study. We offer a very simple tool where you just need to provide basic info about your variables, subjects, and predicted outcomes. The rest is on us. Get a perfect hypothesis in no time!

• 2018/03/28/How-to-write-a-hypothesis

How to write a hypothesis

This is a sticking point for many students. We are used to using and writing questions and statements in day to day communications, as well as reading popular media. But hypotheses (the plural of hypothesis) only rarely float across our desks. So how do we write one, and how do we know if our hypothesis is good?

Although I’m going to write about what I think, there is already some good information out there on the web, and it’s worth looking at this too: (e.g. Wikihow , Wikipedia , etc.). There’s also some dodgy stuff, so read critically.

What is a hypothesis?

A hypothesis is a statement of your research intent. It tells the reader (because just like all of your other written work, it has an audience who reads it), what you planned to do in your research. But there’s a little more to it than this. The hypothesis becomes a part of the scientific method if it is testable, and informed from previous published work on the subject.

Yes, your hypothesis must  be informed by the literature, which is why you spent so much time and effort crafting your introduction to inform your reader of the same. This is also why your hypothesis usually comes at the end of your introduction, because you spend all of the introduction telling your reader about it (see blog entry here ). There’s not much point in writing more after the hypothesis, because once your reader has read that, they are ready to learn about how you went about testing it (in the Materials & Methods). The other important point to make is that the literature should dictate how you write your hypothesis, and the variables that you include. If, for example, you know that temperature is the most important variable but all of the literature suggests that it is oxygen, you can’t ignore oxygen and you should also frame your hypothesis using this variable (you can have more than one hypothesis after all!). In this case, you will also need to provide a sufficient introduction to temperature as a variable to justify its inclusion in your hypothesis. Perversely, your aim is not to prove that your idea is right, but to show that the hypothesis is wrong.

We usually try to write a hypothesis that is falsifiable: i.e. you can prove (usually using statistical tests) that it is not correct (or at least show that the likelihood that it is correct is very low). That’s why it is conventional to provide the ‘Null hypothesis’ that is the falsified version of the statement, suggesting that there is no relationship between the variables you have proposed to measure. The convention is to label this H 0 , while the ‘alternative hypothesis’ (the one that says your variables are related as you suggested) is written as H 1 . You can write you alternative hypothesis to show the directionality of your tested variables, or simply that there is a relationship.

Most importantly, your hypothesis must come first, before you do the experiment or study! Setting the hypothesis after the work is already done is fraudulent, and goes against the scientific method. Obviously, it isn’t fair to pose the hypothesis once you already know the answer. This is why there is so much emphasis put on formulating your hypothesis during your research proposal. Getting it right will determine what you do and how you test it. If you think of an extra hypothesis that would be really useful to test once you’ve already done your study, you can conduct a post hoc test, but this should have more stringent levels of statistical assessment.

Writing a hypothesis isn’t easy, but it is essential and once you’ve understood what to do, most of the rest of what you are writing for should make sense.

What a hypothesis isn’t

It is not a question and so should never have a question mark after it.

It isn’t really a simple prediction: if this then that. You will see many times on the internet that hypotheses are explained in this simple predictive framework. I say that it isn't ' really ' a simple prediction because these are not good hypotheses. They lack the mechanistic and scholarly aspect of a good hypothesis, which is what we want to achieve.

A formulaic way to start writing your hypothesis: “ If… then… because… ”

Above, I emphasised that you must have introduced all the variables that you plan to use to test your hypothesis in your introduction. This usually comes in the second paragraph ( see blog entry here ), where you emphasise the utility of the dependent variable/s (what you are planning to measure) and your independent variable (what you will manipulate). Both of these variables should then feature in your hypothesis. Next, by paragraph four you will have identified the problem that you are interested in tackling. In addition, your introduction will provide all of the pertinent literature that has relevance to this hypothesis, giving the all important context.

A simple way to consider making your hypothesis is to adopt an “ If… then… because… ” construction where you add in your problem statement using your independent variable after ‘ if ’ and your prediction using your dependent variable after ‘ then ’, and finally the expected mechanism after ‘ because ’. Using our example above with the “If… then… because…” construction, we would say: “ If environmental temperatures in which tadpoles develop are increased then tadpole development rate is faster because they follow the classic metabolism of ectotherms”. Both independent variable (temperature) and dependent variable (tadpole development rate) are present in this hypothesis, and the predicted relationship between them is clear. In addition, the causal mechanism is stated. You can watch a video about using the “If… then… because…” construction here , or read more here . I say that this is a formulaic way to start writing your hypothesis, because it usually ends up as an inelegant statement, which can be better refined for a reader. A citation for your stated mechanism might also help clarify exactly where the justification for this comes from.

A good hypothesis will often take an existing hypothesis further, to try to better refine the knowledge on a subject. Hence, it is perfectly acceptable to state that you are building on existing hypotheses (and giving the appropriate statement) when making your own.

How to evaluate your hypothesis

Once you’ve written your hypothesis, how do you decide whether or not it is good? To do this, you might think that you need plenty of experience (and yes, that does help). But really, you just need to look for the elements that are discussed above. So once you’ve written your hypothesis, try to objectively answer the questions below (for more see Bartos 1992 and here ):

• Is there a clear prediction (if… then… statement)?
• Does the prediction use independent and dependent variables correctly?
• Is the mechanism supported by the literature?
• Is the hypothesis testable/falsifiable?
• Does the hypothesis use concise wording and precise terminology?

If your hypothesis meets all of the criteria above, then you’ve done a good job!

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