give examples of how hypothesis lead to new experimentation

15 Hypothesis Examples

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A hypothesis is defined as a testable prediction , and is used primarily in scientific experiments as a potential or predicted outcome that scientists attempt to prove or disprove (Atkinson et al., 2021; Tan, 2022).

In my types of hypothesis article, I outlined 13 different hypotheses, including the directional hypothesis (which makes a prediction about an effect of a treatment will be positive or negative) and the associative hypothesis (which makes a prediction about the association between two variables).

This article will dive into some interesting examples of hypotheses and examine potential ways you might test each one.

Hypothesis Examples

1. “inadequate sleep decreases memory retention”.

Field: Psychology

Type: Causal Hypothesis A causal hypothesis explores the effect of one variable on another. This example posits that a lack of adequate sleep causes decreased memory retention. In other words, if you are not getting enough sleep, your ability to remember and recall information may suffer.

How to Test:

To test this hypothesis, you might devise an experiment whereby your participants are divided into two groups: one receives an average of 8 hours of sleep per night for a week, while the other gets less than the recommended sleep amount.

During this time, all participants would daily study and recall new, specific information. You’d then measure memory retention of this information for both groups using standard memory tests and compare the results.

Should the group with less sleep have statistically significant poorer memory scores, the hypothesis would be supported.

Ensuring the integrity of the experiment requires taking into account factors such as individual health differences, stress levels, and daily nutrition.

Relevant Study: Sleep loss, learning capacity and academic performance (Curcio, Ferrara & De Gennaro, 2006)

2. “Increase in Temperature Leads to Increase in Kinetic Energy”

Field: Physics

Type: Deductive Hypothesis The deductive hypothesis applies the logic of deductive reasoning – it moves from a general premise to a more specific conclusion. This specific hypothesis assumes that as temperature increases, the kinetic energy of particles also increases – that is, when you heat something up, its particles move around more rapidly.

This hypothesis could be examined by heating a gas in a controlled environment and capturing the movement of its particles as a function of temperature.

You’d gradually increase the temperature and measure the kinetic energy of the gas particles with each increment. If the kinetic energy consistently rises with the temperature, your hypothesis gets supporting evidence.

Variables such as pressure and volume of the gas would need to be held constant to ensure validity of results.

3. “Children Raised in Bilingual Homes Develop Better Cognitive Skills”

Field: Psychology/Linguistics

Type: Comparative Hypothesis The comparative hypothesis posits a difference between two or more groups based on certain variables. In this context, you might propose that children raised in bilingual homes have superior cognitive skills compared to those raised in monolingual homes.

Testing this hypothesis could involve identifying two groups of children: those raised in bilingual homes, and those raised in monolingual homes.

Cognitive skills in both groups would be evaluated using a standard cognitive ability test at different stages of development. The examination would be repeated over a significant time period for consistency.

If the group raised in bilingual homes persistently scores higher than the other, the hypothesis would thereby be supported.

The challenge for the researcher would be controlling for other variables that could impact cognitive development, such as socio-economic status, education level of parents, and parenting styles.

Relevant Study: The cognitive benefits of being bilingual (Marian & Shook, 2012)

4. “High-Fiber Diet Leads to Lower Incidences of Cardiovascular Diseases”

Field: Medicine/Nutrition

Type: Alternative Hypothesis The alternative hypothesis suggests an alternative to a null hypothesis. In this context, the implied null hypothesis could be that diet has no effect on cardiovascular health, which the alternative hypothesis contradicts by suggesting that a high-fiber diet leads to fewer instances of cardiovascular diseases.

To test this hypothesis, a longitudinal study could be conducted on two groups of participants; one adheres to a high-fiber diet, while the other follows a diet low in fiber.

After a fixed period, the cardiovascular health of participants in both groups could be analyzed and compared. If the group following a high-fiber diet has a lower number of recorded cases of cardiovascular diseases, it would provide evidence supporting the hypothesis.

Control measures should be implemented to exclude the influence of other lifestyle and genetic factors that contribute to cardiovascular health.

Relevant Study: Dietary fiber, inflammation, and cardiovascular disease (King, 2005)

5. “Gravity Influences the Directional Growth of Plants”

Field: Agronomy / Botany

Type: Explanatory Hypothesis An explanatory hypothesis attempts to explain a phenomenon. In this case, the hypothesis proposes that gravity affects how plants direct their growth – both above-ground (toward sunlight) and below-ground (towards water and other resources).

The testing could be conducted by growing plants in a rotating cylinder to create artificial gravity.

Observations on the direction of growth, over a specified period, can provide insights into the influencing factors. If plants consistently direct their growth in a manner that indicates the influence of gravitational pull, the hypothesis is substantiated.

It is crucial to ensure that other growth-influencing factors, such as light and water, are uniformly distributed so that only gravity influences the directional growth.

6. “The Implementation of Gamified Learning Improves Students’ Motivation”

Field: Education

Type: Relational Hypothesis The relational hypothesis describes the relation between two variables. Here, the hypothesis is that the implementation of gamified learning has a positive effect on the motivation of students.

To validate this proposition, two sets of classes could be compared: one that implements a learning approach with game-based elements, and another that follows a traditional learning approach.

The students’ motivation levels could be gauged by monitoring their engagement, performance, and feedback over a considerable timeframe.

If the students engaged in the gamified learning context present higher levels of motivation and achievement, the hypothesis would be supported.

Control measures ought to be put into place to account for individual differences, including prior knowledge and attitudes towards learning.

Relevant Study: Does educational gamification improve students’ motivation? (Chapman & Rich, 2018)

7. “Mathematics Anxiety Negatively Affects Performance”

Field: Educational Psychology

Type: Research Hypothesis The research hypothesis involves making a prediction that will be tested. In this case, the hypothesis proposes that a student’s anxiety about math can negatively influence their performance in math-related tasks.

To assess this hypothesis, researchers must first measure the mathematics anxiety levels of a sample of students using a validated instrument, such as the Mathematics Anxiety Rating Scale.

Then, the students’ performance in mathematics would be evaluated through standard testing. If there’s a negative correlation between the levels of math anxiety and math performance (meaning as anxiety increases, performance decreases), the hypothesis would be supported.

It would be crucial to control for relevant factors such as overall academic performance and previous mathematical achievement.

8. “Disruption of Natural Sleep Cycle Impairs Worker Productivity”

Field: Organizational Psychology

Type: Operational Hypothesis The operational hypothesis involves defining the variables in measurable terms. In this example, the hypothesis posits that disrupting the natural sleep cycle, for instance through shift work or irregular working hours, can lessen productivity among workers.

To test this hypothesis, you could collect data from workers who maintain regular working hours and those with irregular schedules.

Measuring productivity could involve examining the worker’s ability to complete tasks, the quality of their work, and their efficiency.

If workers with interrupted sleep cycles demonstrate lower productivity compared to those with regular sleep patterns, it would lend support to the hypothesis.

Consideration should be given to potential confounding variables such as job type, worker age, and overall health.

9. “Regular Physical Activity Reduces the Risk of Depression”

Field: Health Psychology

Type: Predictive Hypothesis A predictive hypothesis involves making a prediction about the outcome of a study based on the observed relationship between variables. In this case, it is hypothesized that individuals who engage in regular physical activity are less likely to suffer from depression.

Longitudinal studies would suit to test this hypothesis, tracking participants’ levels of physical activity and their mental health status over time.

The level of physical activity could be self-reported or monitored, while mental health status could be assessed using standard diagnostic tools or surveys.

If data analysis shows that participants maintaining regular physical activity have a lower incidence of depression, this would endorse the hypothesis.

However, care should be taken to control other lifestyle and behavioral factors that could intervene with the results.

Relevant Study: Regular physical exercise and its association with depression (Kim, 2022)

10. “Regular Meditation Enhances Emotional Stability”

Type: Empirical Hypothesis In the empirical hypothesis, predictions are based on amassed empirical evidence . This particular hypothesis theorizes that frequent meditation leads to improved emotional stability, resonating with numerous studies linking meditation to a variety of psychological benefits.

Earlier studies reported some correlations, but to test this hypothesis directly, you’d organize an experiment where one group meditates regularly over a set period while a control group doesn’t.

Both groups’ emotional stability levels would be measured at the start and end of the experiment using a validated emotional stability assessment.

If regular meditators display noticeable improvements in emotional stability compared to the control group, the hypothesis gains credit.

You’d have to ensure a similar emotional baseline for all participants at the start to avoid skewed results.

11. “Children Exposed to Reading at an Early Age Show Superior Academic Progress”

Type: Directional Hypothesis The directional hypothesis predicts the direction of an expected relationship between variables. Here, the hypothesis anticipates that early exposure to reading positively affects a child’s academic advancement.

A longitudinal study tracking children’s reading habits from an early age and their consequent academic performance could validate this hypothesis.

Parents could report their children’s exposure to reading at home, while standardized school exam results would provide a measure of academic achievement.

If the children exposed to early reading consistently perform better acadically, it gives weight to the hypothesis.

However, it would be important to control for variables that might impact academic performance, such as socioeconomic background, parental education level, and school quality.

12. “Adopting Energy-efficient Technologies Reduces Carbon Footprint of Industries”

Field: Environmental Science

Type: Descriptive Hypothesis A descriptive hypothesis predicts the existence of an association or pattern related to variables. In this scenario, the hypothesis suggests that industries adopting energy-efficient technologies will resultantly show a reduced carbon footprint.

Global industries making use of energy-efficient technologies could track their carbon emissions over time. At the same time, others not implementing such technologies continue their regular tracking.

After a defined time, the carbon emission data of both groups could be compared. If industries that adopted energy-efficient technologies demonstrate a notable reduction in their carbon footprints, the hypothesis would hold strong.

In the experiment, you would exclude variations brought by factors such as industry type, size, and location.

13. “Reduced Screen Time Improves Sleep Quality”

Type: Simple Hypothesis The simple hypothesis is a prediction about the relationship between two variables, excluding any other variables from consideration. This example posits that by reducing time spent on devices like smartphones and computers, an individual should experience improved sleep quality.

A sample group would need to reduce their daily screen time for a pre-determined period. Sleep quality before and after the reduction could be measured using self-report sleep diaries and objective measures like actigraphy, monitoring movement and wakefulness during sleep.

If the data shows that sleep quality improved post the screen time reduction, the hypothesis would be validated.

Other aspects affecting sleep quality, like caffeine intake, should be controlled during the experiment.

Relevant Study: Screen time use impacts low‐income preschool children’s sleep quality, tiredness, and ability to fall asleep (Waller et al., 2021)

14. Engaging in Brain-Training Games Improves Cognitive Functioning in Elderly

Field: Gerontology

Type: Inductive Hypothesis Inductive hypotheses are based on observations leading to broader generalizations and theories. In this context, the hypothesis deduces from observed instances that engaging in brain-training games can help improve cognitive functioning in the elderly.

A longitudinal study could be conducted where an experimental group of elderly people partakes in regular brain-training games.

Their cognitive functioning could be assessed at the start of the study and at regular intervals using standard neuropsychological tests.

If the group engaging in brain-training games shows better cognitive functioning scores over time compared to a control group not playing these games, the hypothesis would be supported.

15. Farming Practices Influence Soil Erosion Rates

Type: Null Hypothesis A null hypothesis is a negative statement assuming no relationship or difference between variables. The hypothesis in this context asserts there’s no effect of different farming practices on the rates of soil erosion.

Comparing soil erosion rates in areas with different farming practices over a considerable timeframe could help test this hypothesis.

If, statistically, the farming practices do not lead to differences in soil erosion rates, the null hypothesis is accepted.

However, if marked variation appears, the null hypothesis is rejected, meaning farming practices do influence soil erosion rates. It would be crucial to control for external factors like weather, soil type, and natural vegetation.

The variety of hypotheses mentioned above underscores the diversity of research constructs inherent in different fields, each with its unique purpose and way of testing.

While researchers may develop hypotheses primarily as tools to define and narrow the focus of the study, these hypotheses also serve as valuable guiding forces for the data collection and analysis procedures, making the research process more efficient and direction-focused.

Hypotheses serve as a compass for any form of academic research. The diverse examples provided, from Psychology to Educational Studies, Environmental Science to Gerontology, clearly demonstrate how certain hypotheses suit specific fields more aptly than others.

It is important to underline that although these varied hypotheses differ in their structure and methods of testing, each endorses the fundamental value of empiricism in research. Evidence-based decision making remains at the heart of scholarly inquiry, regardless of the research field, thus aligning all hypotheses to the core purpose of scientific investigation.

Testing hypotheses is an essential part of the scientific method . By doing so, researchers can either confirm their predictions, giving further validity to an existing theory, or they might uncover new insights that could potentially shift the field’s understanding of a particular phenomenon. In either case, hypotheses serve as the stepping stones for scientific exploration and discovery.

Atkinson, P., Delamont, S., Cernat, A., Sakshaug, J. W., & Williams, R. A. (2021).  SAGE research methods foundations . SAGE Publications Ltd.

Curcio, G., Ferrara, M., & De Gennaro, L. (2006). Sleep loss, learning capacity and academic performance.  Sleep medicine reviews ,  10 (5), 323-337.

Kim, J. H. (2022). Regular physical exercise and its association with depression: A population-based study short title: Exercise and depression.  Psychiatry Research ,  309 , 114406.

King, D. E. (2005). Dietary fiber, inflammation, and cardiovascular disease.  Molecular nutrition & food research ,  49 (6), 594-600.

Marian, V., & Shook, A. (2012, September). The cognitive benefits of being bilingual. In Cerebrum: the Dana forum on brain science (Vol. 2012). Dana Foundation.

Tan, W. C. K. (2022). Research Methods: A Practical Guide For Students And Researchers (Second Edition) . World Scientific Publishing Company.

Waller, N. A., Zhang, N., Cocci, A. H., D’Agostino, C., Wesolek‐Greenson, S., Wheelock, K., … & Resnicow, K. (2021). Screen time use impacts low‐income preschool children’s sleep quality, tiredness, and ability to fall asleep. Child: care, health and development, 47 (5), 618-626.

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20 Hypothesis Examples

A hypothesis It is an idea that arises to explain a certain phenomenon or situation and that is tried to prove or reject through experimentation or other methods. For instance: School dropout is the product of bad public policies.

The hypothesis is one of the first steps of the scientific method and is the axis on which the entire investigative process is directed. After investigating, the researcher asks questions and then develops a hypothesis that is understood as the possible explanation for the questions posed.

The hypotheses are formulated based on data or information available to the scientist after an exhaustive investigation that allows him to suppose relationships between variables. These hypotheses are then verified or refuted from the data produced by experimentation.

In addition, hypotheses are formulated by individuals on a day-to-day basis to suppose or give an estimated or indicative answer about something. That is, any conjecture is known as a hypothesis (regardless of whether the verification was investigative or experimental), since any statement made on the basis of a situation for which there are no certainties is a hypothetical statement. Then this hypothesis can be verified by direct observation or on the basis of information obtained or experimentation.

Characteristics of the hypothesis

Some characteristics of the hypotheses are:

• They are unverified statements . Information is missing or experimentation is necessary.
• They can be proven or disproved . They will be verified to the extent that the foregoing is fulfilled. Within scientific research, a hypothesis will become scientific knowledge if it can be generalized to all times and places.
• They are made from information or data obtained . Hypotheses are posed and formulated once the variables have been observed and analyzed and a possible conclusion is reached.
• They are formulated in a positive and simple way . Hypotheses are simple statements that relate variables or establish causes and consequences.
• They establish a possible relationship between two elements . Hypotheses can also explain something that happens to one item from something that happens to another.
• Be credible . The sequence of experiments or hypothesis testing cannot produce a relationship that is not actually true.
• Cover a portion of the universe . The hypotheses must be specific and objective.
• Be verifiable . Hypotheses can be tested or rejected by direct observation (in the case of hypotheses that lack scientific backing) or by experimentation.

Types of research hypotheses

Research hypotheses are those that study two or more variables and are usually supported by scientific research. They may be:

• Causal hypotheses . When the variables have a causal relationship with each other. For instance: The egg did not cook because the water was cold.
• Relational hypothesis . When the variables have some kind of relationship with each other. For instance: California’s climate is warmer than Oregon.
• Descriptive hypotheses . When they describe a variable or situation. For instance: The students of this institution are all men.
• Null hypotheses . When they do not suppose any relationship between the variables studied. For instance: There is no relationship between the winds this morning and the rain at noon.

Steps to make a scientific hypothesis

• Define the topic in detail . For this you must gather information and research on the topic of interest.
• Develop an investigative question . The information gathered will raise a question or question to be solved.
• Investigate possible answers to the question . In this step, all variables must be taken into account and the idea that is the most probable explanation must be chosen.
• Formulate the hypothesis . The hypothesis must be established and its scope determined in order to then be able to submit it to an analysis or experimentation that determines the validity or not of the hypothesis presented.

Examples of scientific hypotheses

• Tobacco use in the early teenage years is four times more harmful than in adulthood.
• The societies with the least social conflict are, at the same time, the societies with the greatest tendency to suicide and depression.
• Within this organization, women’s wages are below those of men.
• Today’s cars use 20% more energy than they did twenty years ago.
• The most stable political systems are those with the toughest and most rigid rulers.
• These sudden changes in temperature are the product of global warming.
• Women over 40 have better eating behaviors than men of the same age.
• The consumption of 1 liter of water daily improves the heart rate.
• A reduction in subsidies will generate an economic contraction of 4%.
• A body totally or partially submerged in a static fluid will be pushed with a force equal to the weight of the volume of fluid displaced by said object.

Examples of general and everyday hypotheses

• Many guitarists are good, but he will surely win the award.
• When the level of social unrest increases, their political propaganda will no longer work.
• If I put in a lot of effort, I will be able to buy a new car.
• The player who left the game on a stretcher must have been injured.
• The lawyer is convinced of the innocence of his client.
• The bus is delayed, there must have been an accident on the avenue.
• Due to the rain, surely many people do not attend the concert today.
• We believe that you are insolvent, so we cannot lend you more money.
• The tree must have fallen in last night’s storm.
• I think the teacher will not come today because she is very punctual and has not arrived yet.

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Science Hypothesis

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Hypothesis are the bedrock of scientific investigation, guiding researchers toward understanding the unknown. Crafting effective science hypotheses involves precise formulation and prediction. This hypothesis statement guide delves into the intricacies of constructing science hypothesis statements, offering practical examples and valuable tips to ensure your hypothesis stand strong against the rigors of experimentation and analysis.

What is Science Hypothesis? – Definition

A science hypothesis is a proposed explanation or educated guess that can be tested through experimentation or observation. It serves as a preliminary assumption or prediction about a phenomenon, often derived from existing knowledge or theories. Science hypotheses are essential for guiding research and helping scientists investigate the validity of their predictions.

What is an example of a hypothesis statement in science?

Example of a hypothesis statement in science: “If the temperature of water increases, then the rate of plant growth will also increase.” This hypothesis predicts a cause-and-effect relationship between water temperature and plant growth, which can be tested through controlled experiments.

100 Science Hypothesis Statement Examples

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Science hypotheses lay the foundation for empirical exploration. These Thesis statements predict outcomes based on existing knowledge and guide research. Explore a variety of science hypothesis examples across different disciplines, showcasing the diverse ways scientists propose, test, and validate their assumptions. From physics to biology, chemistry to astronomy, delve into these examples that highlight the essence of scientific inquiry and discovery.

• Physics : If the mass of an object increases, its gravitational pull on another object will also increase.
• Biology : If plants are exposed to different light wavelengths, then the one exposed to red light will exhibit the highest growth rate.
• Chemistry : If the concentration of a reactant increases, then the rate of the chemical reaction will also increase.
• Astronomy : If the distance between two galaxies decreases, then their gravitational attraction will intensify.
• Geology : If the temperature of a rock sample increases, then its density will decrease due to expansion.
• Psychology : If individuals are exposed to positive affirmations, then their self-esteem scores will improve.
• Sociology : If economic inequality increases, then crime rates within a community will also rise.
• Environmental Science : If pollution levels decrease in a river, then the diversity of aquatic species will increase.
• Computer Science : If the processing speed of a computer chip increases, then the execution time of a software program will decrease.
• Meteorology : If atmospheric pressure drops significantly, then the likelihood of stormy weather conditions will rise.
• Neuroscience : If individuals engage in regular meditation, then their brain’s gray matter volume in regions associated with mindfulness will increase.
• Economics : If interest rates decrease, then consumer spending will rise due to increased borrowing.
• Anthropology : If a society’s cultural diversity increases, then its acceptance of differing norms and values will also grow.
• Zoology : If predators are introduced to an ecosystem, then the population of prey species will decline.
• Medical Research : If a new drug is administered, then patients with a specific medical condition will experience a reduction in symptoms.
• Nutrition Science : If individuals consume a diet high in antioxidants, then their risk of developing certain chronic diseases will decrease.
• Materials Science : If the temperature of a metal is lowered, then its electrical conductivity will decrease due to reduced kinetic energy.
• Political Science : If voter education initiatives increase, then voter turnout rates in elections will also rise.
• Geography : If urbanization expands in a region, then the average local temperature will increase due to the heat island effect.
• Ecology : If a keystone species is removed from an ecosystem, then the overall biodiversity of that ecosystem will be negatively impacted.
• Medieval History : If trade routes between two civilizations strengthen, then cultural exchange and technological advancements will flourish.
• Microbiology : If a specific bacterium is introduced to a microbial community, then it will outcompete other species for resources.
• Oceanography : If ocean temperatures rise, then coral reefs will experience bleaching due to the loss of symbiotic algae.
• Education : If class sizes are reduced, then student engagement and learning outcomes will improve.
• Genetics : If individuals inherit two recessive alleles for a particular trait, then they will exhibit the trait phenotypically.
• Criminology : If community policing initiatives are implemented, then the crime rate in neighborhoods will decrease due to improved trust between law enforcement and residents.
• Botany : If plants are exposed to varying levels of nutrients, then their growth rate and overall health will be affected accordingly.
• Epidemiology : If individuals are vaccinated against a specific virus, then the incidence of that virus in the population will decline.
• Architecture : If buildings are designed with energy-efficient features, then their energy consumption and environmental impact will be reduced.
• Literary Studies : If readers are exposed to diverse genres of literature, then their vocabulary and literary comprehension will expand.
• Mechanical Engineering : If the surface area of a heat exchanger is increased, then its efficiency in transferring thermal energy will improve.
• Artificial Intelligence : If a machine learning algorithm is trained on a larger dataset, then its accuracy in making predictions will increase.
• Sports Science : If athletes incorporate specific pre-game rituals, then their performance and focus during competitions will improve.
• Archaeology : If a new excavation site is discovered, then artifacts and evidence of past civilizations will be uncovered.
• Film Studies : If films use non-linear storytelling techniques, then audience engagement and interpretation will become more complex.
• Fashion Design : If clothing materials with better breathability are used, then wearers’ comfort levels in hot weather will increase.
• Music Psychology : If listeners are exposed to music with a fast tempo, then their heart rate and energy levels will be positively affected.
• Environmental Engineering : If a wastewater treatment system is upgraded, then the water quality of nearby rivers and streams will improve.
• Philosophy : If ethical dilemmas are discussed openly, then individuals’ moral reasoning and decision-making skills will become more refined.
• Cognitive Science : If individuals practice mindfulness meditation, then their attention span and cognitive control will enhance.
• Political Economy : If trade barriers between two countries are lifted, then their economic interdependence and cooperation will strengthen.
• Agricultural Science : If certain crops are rotated in a field, then soil fertility and nutrient content will be better maintained.
• Cultural Anthropology : If cultural norms change to value gender equality, then the division of labor and social roles will evolve accordingly.
• Linguistics : If a language’s phonetic structure is altered, then the perception and articulation of speech sounds will be affected.
• Religious Studies : If religious festivals are celebrated widely, then social cohesion and a sense of community among participants will increase.
• Urban Planning : If public transportation infrastructure is improved, then the use of private vehicles and traffic congestion will decrease.
• Renewable Energy : If solar panel efficiency increases, then the cost-effectiveness of solar energy as a power source will improve.
• Sustainable Agriculture : If organic farming practices are adopted, then soil health and biodiversity in agricultural fields will be enhanced.
• Human Genetics : If a specific gene mutation is present, then the likelihood of developing a hereditary disease will be higher.
• Space Exploration : If a spacecraft is sent to a distant planet, then the data collected will provide insights into its composition and environment.
• Cultural Studies : If a society values inclusivity in its media representations, then stereotypes and biases will be challenged.
• Quantum Physics : If two entangled particles are measured, then the measurement of one particle will instantaneously affect the state of the other particle, regardless of distance.
• Social Work : If support systems are established for individuals facing addiction, then their likelihood of successful recovery will increase.
• Civil Engineering : If a bridge is constructed using specific materials and design principles, then its load-bearing capacity and structural integrity will be maximized.
• Educational Technology : If interactive learning platforms are integrated into classrooms, then students’ engagement and retention of concepts will rise.
• Animal Behavior : If a specific stimulus is introduced to an animal’s environment, then its behavioral response will indicate whether the stimulus is perceived as positive or negative.
• Public Health : If a vaccination campaign targets a high percentage of the population, then the spread of a contagious disease will be curbed.
• Forensic Science : If DNA evidence is analyzed from a crime scene, then it can be matched to potential suspects or used to exonerate individuals.
• Game Design : If a game incorporates branching storylines, then players’ choices will lead to multiple possible outcomes and endings.
• Gender Studies : If gender stereotypes are challenged in educational settings, then students’ understanding of gender roles and identities will evolve.
• Particle Physics : If a new particle is discovered in particle accelerator experiments, then it may contribute to our understanding of fundamental forces.
• Culinary Science : If cooking techniques are adjusted, then the texture and flavor of a dish will be enhanced.
• Developmental Psychology : If children are exposed to early childhood education programs, then their cognitive and social development will be positively influenced.
• Journalism : If journalists provide unbiased coverage of events, then the public’s perception and understanding of news stories will be more accurate.
• Business Management : If a company implements remote work policies, then employees’ job satisfaction and productivity will be impacted.
• Astronomy : If a telescope observes a distant celestial object, then its light spectrum can reveal information about its composition and distance.
• Climate Science : If greenhouse gas emissions continue to rise, then global temperatures will increase, leading to more frequent and severe climate events.
• Molecular Biology : If a specific gene is mutated, then the protein it codes for may lose its function, leading to a genetic disorder.
• Urban Sociology : If urban planning focuses on mixed-use development, then neighborhoods will become more walkable and vibrant.
• Environmental Science : If deforestation continues in a particular region, then biodiversity loss and habitat destruction will result.
• Educational Psychology : If students receive constructive feedback, then their academic performance and self-esteem will improve.
• Sports Nutrition : If athletes consume a balanced diet, then their energy levels and physical performance will be optimized.
• Industrial Engineering : If a manufacturing process is streamlined, then production efficiency and cost-effectiveness will increase.
• Climate Change Mitigation : If renewable energy sources replace fossil fuels, then carbon emissions and air pollution will decrease.
• Criminal Justice : If restorative justice programs are implemented, then recidivism rates among offenders will decrease.
• Cognitive Neuroscience : If brain imaging techniques are used, then neural activity patterns associated with memory retrieval can be identified.
• Environmental Policy : If conservation policies are enforced, then endangered species populations will have a chance to recover.
• Tourism Management : If sustainable tourism practices are adopted, then the negative impact of tourism on local ecosystems will be minimized.
• Public Opinion Research : If surveys are conducted on political preferences, then insights into voter behavior and attitudes can be gained.
• Sociolinguistics : If language use changes over time, then linguistic patterns and dialects in a community may evolve.
• Consumer Behavior : If marketing strategies incorporate social media influencers, then consumer purchasing decisions will be influenced.
• Digital Communication : If online privacy measures are strengthened, then users’ data security and trust in digital platforms will increase.
• Cancer Research : If a specific genetic mutation is identified, then targeted therapies can be developed to treat the cancer associated with that mutation.
• Human Rights Advocacy : If educational campaigns raise awareness about human rights violations, then public pressure on governments to address these issues will rise.
• Educational Assessment : If standardized tests are redesigned to focus on critical thinking skills, then students’ analytical abilities will be better evaluated.
• Epidemiology : If a specific virus spreads within a community, then the rate of infection and transmission can be studied to develop effective containment strategies.
• Cognitive Psychology : If memory recall is examined under different conditions, then the factors influencing memory retrieval can be identified.
• Financial Economics : If interest rates are lowered by the central bank, then borrowing costs for businesses and individuals will decrease.
• Marine Biology : If ocean temperatures rise due to climate change, then coral bleaching events will become more frequent, leading to coral reef degradation.
• Political Science : If voter turnout is influenced by campaign advertising, then the correlation between media exposure and voting behavior can be analyzed.
• Clinical Psychology : If cognitive-behavioral therapy is administered to individuals with anxiety disorders, then their symptoms will show a reduction.
• Public Policy : If a government enforces stricter regulations on smoking in public spaces, then the prevalence of smoking-related health issues will decline.
• Material Science : If a new material is developed with specific properties, then its potential applications in various industries can be explored.
• Language Acquisition : If children are exposed to multiple languages in their early years, then their linguistic skills may develop differently compared to monolingual children.
• Tourism Economics : If travel restrictions are lifted, then the recovery of the tourism industry and its contribution to the local economy can be assessed.
• Behavioral Economics : If individuals are given incentives to make environmentally friendly choices, then the impact of economic incentives on behavior can be studied.
• Educational Technology : If online learning platforms are used in classrooms, then their effect on student engagement and academic performance can be evaluated.
• Health Policy : If universal healthcare coverage is implemented, then access to medical services and health outcomes for the population can be improved.
• Agricultural Economics : If crop yields are compared between traditional farming methods and modern agricultural practices, then the efficiency of different approaches can be determined.
• Literary Analysis : If a specific theme is analyzed across different literary works, then the ways in which authors address and convey that theme can be explored.

Science Hypothesis Statement Examples for Psychology

These psychology hypothesis pertain to human behaviors, emotions, or cognitive processes. They are tailored to the field of psychology, which studies the human mind and behavior. For instance, “Effects of Sleep on Memory” posits a connection between sleep duration and memory performance.

• Effects of Sleep on Memory : People who sleep 8 hours per night will perform better on memory tests compared to those who sleep only 4 hours.
• Role of Colors in Mood Regulation : Exposure to blue light will decrease feelings of sadness in depressed individuals.
• Childhood Attachment and Adult Relationships : Individuals with secure childhood attachments will have more stable romantic relationships in adulthood.
• Influence of Music on Productivity : Listening to classical music while working increases task completion rates among office workers.
• Gaming and Reaction Time : Regular gamers will have quicker reaction times than non-gamers in response to unexpected stimuli.
• Effects of Meditation on Stress : Individuals who practice daily meditation will report lower stress levels compared to those who don’t meditate.
• Social Media Usage and Loneliness : High usage of social media correlates with increased feelings of loneliness in teenagers.
• Class Size and Student Performance : Students in smaller class sizes will score higher on standardized tests than students in larger class sizes.
• Scent and Memory Recall : People exposed to a specific scent during learning will recall information better when the same scent is present during retrieval.
• Financial Incentives and Motivation : Providing financial incentives will increase motivation for completing mundane tasks.

Simple Science Hypothesis Statement Examples

These are basic and straightforward scientific hypotheses that cover various fields, such as biology or physics. They’re easy to understand even for people without much scientific background. For instance, the simple hypothesis tatement about “Plant Growth” directly relates the use of fertilizer to plant height.

• Plant Growth : Adding fertilizer will make plants grow taller.
• Solar Energy : Increasing sunlight exposure will increase the voltage output of a solar cell.
• Density : Objects made of metal will sink in water.
• Digestion : Enzyme supplements will increase the speed of food digestion.
• Osmosis : Potatoes placed in salt water will shrink due to loss of water.
• Evaporation : Water will evaporate faster on a hot day compared to a cold day.
• Nutrition : Plants given sugar water will develop yellow leaves.
• Magnetism : Increasing the temperature of a magnet will decrease its magnetic strength.
• Conduction : Metals will conduct electricity better than plastics.
• Reflection : Shiny surfaces reflect more light than dull surfaces.

Strong Science Hypothesis Statement Examples

These are more detailed and specific hypotheses, often relating to a well-defined scientific question. They may also suggest a precise outcome or relationship. For example, “Vaccination and Immunity” indicates a specific result (production of specific antibodies) in response to a defined action (vaccinating mice).

• Environmental Toxins and Cell Growth : Exposure to specific environmental toxins will inhibit the division of cells in an organism.
• Nutrition and Cognitive Performance : Diets rich in omega-3 fatty acids will significantly enhance cognitive performance in adults over 60.
• Genetic Mutations and Disease Resistance : Specific genetic mutations in fruit flies will confer resistance to a particular pesticide.
• Neurotransmitters and Behavior : An increase in serotonin levels in the brain will lead to a decrease in aggressive behaviors in rats.
• Plant Pathogens and Resistance : Tomato plants genetically modified to express the XYZ gene will resist infection from the ABC pathogen more effectively than non-modified plants.
• Vaccination and Immunity : Vaccinating mice with a particular strain of virus will lead to the production of specific antibodies that prevent future infections.
• Hormonal Levels and Bone Density : Post-menopausal women with decreased estrogen levels will have a significant reduction in bone density compared to pre-menopausal women.
• Enzyme Concentration and Reaction Rate : Doubling the concentration of an enzyme in a solution will double the rate of the substrate’s conversion to the product.
• Climate Change and Coral Bleaching : An increase in sea surface temperature by 2°C will lead to a 50% increase in coral bleaching events.
• Pesticides and Pollinator Health : Exposure to the pesticide DEF will reduce the foraging ability of honeybees by at least 30%.

Scientific Hypothesis Statement Examples

These are broader scientific hypothesis applicable to different scientific disciplines. They’re structured to make clear, testable predictions about the relationship between variables. “Bacterial Growth,” for instance, predicts the outcome of bacteria exposed to UV light.

• Bacterial Growth : Bacteria exposed to ultraviolet (UV) light will have a reduced growth rate compared to those not exposed to UV light.
• Antibiotic Resistance : Overuse of antibiotics in livestock will lead to an increase in antibiotic-resistant bacteria in humans.
• Evolutionary Adaptation : Birds with longer beaks will have an advantage in accessing food after a drastic environmental change.
• Photosynthesis Rate : Plants grown under red light will have a lower rate of photosynthesis compared to those grown under blue light.
• Stem Cell Differentiation : The presence of growth factor X will guide stem cells to differentiate into nerve cells more frequently than muscle cells.
• Ozone Layer and UV Radiation : Depletion of the ozone layer will result in increased UV radiation levels on Earth’s surface.
• Protein Folding : Mutation at position 123 in protein Z will lead to a misfolded protein structure.
• Water Quality and Fish Health : Rivers with high levels of industrial pollutants will have a reduced fish population due to compromised gill functionality.
• Seismic Activity and Plate Tectonics : Regions located at the boundaries of tectonic plates will experience more frequent and stronger earthquakes.
• Drug Efficacy : Patients treated with drug Y will recover from infection twice as fast as those treated with a placebo.

Alternative Hypothesis Statement Examples for Science

The alternative hypothesis states that there is a statistically significant relationship between two variables. It’s what you might want to prove or demonstrate. For example, the hypothesis about “Green Tea and Metabolism” suggests that drinking green tea can have a positive effect on metabolic rates.

• Dietary Supplements and Energy Levels : Consuming a daily vitamin B12 supplement will increase energy levels in vegans.
• Soil Type and Crop Yield : Sandy soil will produce a lower maize yield than loamy soil.
• Air Pollution and Respiratory Diseases : Living in areas with higher particulate matter (PM2.5) levels will increase the incidence of respiratory diseases.
• Green Tea and Metabolism : Drinking green tea daily will increase metabolic rates in adults.
• Exercise and Brain Health : Engaging in regular aerobic exercise will increase cognitive function in older adults.
• Artificial Sweeteners and Appetite : Consuming artificial sweeteners will increase appetite in individuals.
• Forest Density and Wildlife Diversity : Forests with higher tree density will support a more diverse range of wildlife.
• Hydration and Skin Health : Drinking at least 2 liters of water daily will improve skin elasticity.
• Biofuels and Engine Performance : Engines running on biofuel will have a higher fuel efficiency than those running on traditional petroleum fuels.
• Artificial Light and Plant Growth : Plants grown under LED lights will have a faster growth rate than those grown under fluorescent lights.

Null Hypothesis Statement Examples for Science

The null hypothesis posits that there is no relationship between two variables. It’s the statement you want to test against. Scientists often set out to reject the null hypothesis to demonstrate there’s a relationship. For instance, “Diet and Weight Loss” asserts there’s no difference in weight loss outcomes between two diet types.

• Diet and Weight Loss : There is no difference in weight loss between individuals on a low-carb diet and those on a low-fat diet.
• Antibacterial Soap and Hand Hygiene : Using antibacterial soap does not decrease the number of bacteria on hands compared to using regular soap.
• Meditation and Blood Pressure : There is no difference in blood pressure levels between individuals who meditate daily and those who don’t.
• Organic Foods and Nutrient Content : Organic fruits and vegetables have the same nutrient content as non-organic fruits and vegetables.
• Pain Relievers and Pain Reduction : Over-the-counter pain reliever X does not reduce pain more effectively than a placebo.
• Educational Method and Learning : There is no difference in learning outcomes between students taught using method A and those taught using method B.
• Herbal Treatment and Sleep Duration : Herbal treatment Y does not increase sleep duration compared to a placebo.
• Sunscreen and Sunburn : There is no difference in sunburn incidence between individuals using sunscreen with SPF 30 and those using sunscreen with SPF 50.
• Caffeine and Alertness : Consuming caffeine does not increase alertness levels compared to not consuming caffeine.
• Probiotics and Gut Health : Taking daily probiotics does not increase the diversity of gut bacteria compared to not taking probiotics.

What is a good hypothesis for a science project?

A good hypothesis is a fundamental cornerstone for any scientific project. It provides direction for your research, helping you to focus your investigations and understand the potential outcomes. Here’s what characterizes a good hypothesis:

• Testable : A good hypothesis must be something that can be supported or refuted through experimentation, observation, or analysis.
• Clear and Concise : It should be straightforward and to the point, making it easier for you or others to test.
• Logical : It should make logical sense, building upon existing knowledge and literature.
• Specific : The hypothesis should clearly identify the variables and the relationship between them.
• Relevant : It should be pertinent to the subject matter and not diverge into unrelated areas.
• Predictive : It should make a clear prediction about what you expect to happen in your study.

How do you write a scientific hypothesis statement? – A Step by Step Guide

• Identify Your Research Question : Before you can draft a hypothesis, you need to determine what you’re trying to answer. For example, “Does the type of soil affect plant growth?”
• Perform Preliminary Research : Understand existing literature on the topic. This will help ensure that your hypothesis is original and rooted in current understanding.
• Independent Variable (what you change): e.g., type of soil.
• Dependent Variable (what you measure): e.g., plant growth.
• Make a Prediction : Based on your research, predict the relationship between your variables.
• If : Describes the change or treatment (independent variable).
• Then : Predicts the outcome (dependent variable).
• Because : Provides a rationale based on your background research. E.g., “If a plant is grown in sandy soil, then it will grow slower than in loamy soil, because sandy soil retains less water.”
• Keep it Simple : Avoid complex sentences or jargon. Your hypothesis should be understandable even to someone not in your field.
• Review and Revise : Once drafted, revisit your hypothesis. Ensure it aligns with your research question and that it remains clear and testable.

Tips for Writing Science Hypothesis

• Start with Curiosity : Your initial question should stem from genuine curiosity. It might begin as a broad query which you then refine.
• Use Open-Ended Questions : Start your question with words like “How,” “What,” or “Why.” These types of questions don’t presuppose an answer and lead to more in-depth investigation.
• One Variable at a Time : Especially for beginner projects, limit your hypothesis to one independent variable to keep your study focused and manageable.
• Avoid Biased Language : Your hypothesis should not show any personal biases. Instead of “I believe” or “I think,” use neutral terms.
• Stay Relevant to Available Tools and Resources : Ensure that you can test your hypothesis with the tools, time, and resources available to you.
• Peer Review : Before finalizing your question and hypothesis, have a peer or mentor review it. They might catch ambiguities or complexities you missed.
• Be Ready to Accept Any Outcome : A common mistake is becoming too attached to proving your hypothesis right. Remember, disproving a hypothesis can be just as valuable as proving it.

By carefully crafting your research question and hypothesis, you’ll set a solid foundation for your science project. Whether your results support or challenge your initial predictions, you’ll contribute to the vast and ever-growing body of scientific knowledge.

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The Scientific Method Tutorial

The scientific method, steps in the scientific method.

There is a great deal of variation in the specific techniques scientists use explore the natural world. However, the following steps characterize the majority of scientific investigations:

Step 1: Make observations Step 2: Propose a hypothesis to explain observations Step 3: Test the hypothesis with further observations or experiments Step 4: Analyze data Step 5: State conclusions about hypothesis based on data analysis

Each of these steps is explained briefly below, and in more detail later in this section.

Step 1: Make observations

A scientific inquiry typically starts with observations. Often, simple observations will trigger a question in the researcher's mind.

Example: A biologist frequently sees monarch caterpillars feeding on milkweed plants, but rarely sees them feeding on other types of plants. She wonders if it is because the caterpillars prefer milkweed over other food choices.

Step 2: Propose a hypothesis

The researcher develops a hypothesis (singular) or hypotheses (plural) to explain these observations. A hypothesis is a tentative explanation of a phenomenon or observation(s) that can be supported or falsified by further observations or experimentation.

Example: The researcher hypothesizes that monarch caterpillars prefer to feed on milkweed compared to other common plants. (Notice how the hypothesis is a statement, not a question as in step 1.)

Step 3: Test the hypothesis

The researcher makes further observations and/or may design an experiment to test the hypothesis. An experiment is a controlled situation created by a researcher to test the validity of a hypothesis. Whether further observations or an experiment is used to test the hypothesis will depend on the nature of the question and the practicality of manipulating the factors involved.

Example: The researcher sets up an experiment in the lab in which a number of monarch caterpillars are given a choice between milkweed and a number of other common plants to feed on.

Step 4: Analyze data

The researcher summarizes and analyzes the information, or data, generated by these further observations or experiments.

Example: In her experiment, milkweed was chosen by caterpillars 9 times out of 10 over all other plant selections.

Step 5: State conclusions

The researcher interprets the results of experiments or observations and forms conclusions about the meaning of these results. These conclusions are generally expressed as probability statements about their hypothesis.

Example: She concludes that when given a choice, 90 percent of monarch caterpillars prefer to feed on milkweed over other common plants.

Often, the results of one scientific study will raise questions that may be addressed in subsequent research. For example, the above study might lead the researcher to wonder why monarchs seem to prefer to feed on milkweed, and she may plan additional experiments to explore this question. For example, perhaps the milkweed has higher nutritional value than other available plants.

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The Scientific Method Flowchart

The steps in the scientific method are presented visually in the following flow chart. The question raised or the results obtained at each step directly determine how the next step will proceed. Following the flow of the arrows, pass the cursor over each blue box. An explanation and example of each step will appear. As you read the example given at each step, see if you can predict what the next step will be.

Activity: Apply the Scientific Method to Everyday Life Use the steps of the scientific method described above to solve a problem in real life. Suppose you come home one evening and flick the light switch only to find that the light doesn’t turn on. What is your hypothesis? How will you test that hypothesis? Based on the result of this test, what are your conclusions? Follow your instructor's directions for submitting your response.

The above flowchart illustrates the logical sequence of conclusions and decisions in a typical scientific study. There are some important points to note about this process:

1. The steps are clearly linked.

The steps in this process are clearly linked. The hypothesis, formed as a potential explanation for the initial observations, becomes the focus of the study. The hypothesis will determine what further observations are needed or what type of experiment should be done to test its validity. The conclusions of the experiment or further observations will either be in agreement with or will contradict the hypothesis. If the results are in agreement with the hypothesis, this does not prove that the hypothesis is true! In scientific terms, it "lends support" to the hypothesis, which will be tested again and again under a variety of circumstances before researchers accept it as a fairly reliable description of reality.

2. The same steps are not followed in all types of research.

The steps described above present a generalized method followed in a many scientific investigations. These steps are not carved in stone. The question the researcher wishes to answer will influence the steps in the method and how they will be carried out. For example, astronomers do not perform many experiments as defined here. They tend to rely on observations to test theories. Biologists and chemists have the ability to change conditions in a test tube and then observe whether the outcome supports or invalidates their starting hypothesis, while astronomers are not able to change the path of Jupiter around the Sun and observe the outcome!

3. Collected observations may lead to the development of theories.

When a large number of observations and/or experimental results have been compiled, and all are consistent with a generalized description of how some element of nature operates, this description is called a theory. Theories are much broader than hypotheses and are supported by a wide range of evidence. Theories are important scientific tools. They provide a context for interpretation of new observations and also suggest experiments to test their own validity. Theories are discussed in more detail in another section.

The Scientific Method in Detail

In the sections that follow, each step in the scientific method is described in more detail.

Step 1: Observations

Observations in science.

An observation is some thing, event, or phenomenon that is noticed or observed. Observations are listed as the first step in the scientific method because they often provide a starting point, a source of questions a researcher may ask. For example, the observation that leaves change color in the fall may lead a researcher to ask why this is so, and to propose a hypothesis to explain this phenomena. In fact, observations also will provide the key to answering the research question.

In science, observations form the foundation of all hypotheses, experiments, and theories. In an experiment, the researcher carefully plans what observations will be made and how they will be recorded. To be accepted, scientific conclusions and theories must be supported by all available observations. If new observations are made which seem to contradict an established theory, that theory will be re-examined and may be revised to explain the new facts. Observations are the nuts and bolts of science that researchers use to piece together a better understanding of nature.

Observations in science are made in a way that can be precisely communicated to (and verified by) other researchers. In many types of studies (especially in chemistry, physics, and biology), quantitative observations are used. A quantitative observation is one that is expressed and recorded as a quantity, using some standard system of measurement. Quantities such as size, volume, weight, time, distance, or a host of others may be measured in scientific studies.

Some observations that researchers need to make may be difficult or impossible to quantify. Take the example of color. Not all individuals perceive color in exactly the same way. Even apart from limiting conditions such as colorblindness, the way two people see and describe the color of a particular flower, for example, will not be the same. Color, as perceived by the human eye, is an example of a qualitative observation.

Qualitative observations note qualities associated with subjects or samples that are not readily measured. Other examples of qualitative observations might be descriptions of mating behaviors, human facial expressions, or "yes/no" type of data, where some factor is present or absent. Though the qualities of an object may be more difficult to describe or measure than any quantities associated with it, every attempt is made to minimize the effects of the subjective perceptions of the researcher in the process. Some types of studies, such as those in the social and behavioral sciences (which deal with highly variable human subjects), may rely heavily on qualitative observations.

Question: Why are observations important to science?

Limits of Observations

Because all observations rely to some degree on the senses (eyes, ears, or steady hand) of the researcher, complete objectivity is impossible. Our human perceptions are limited by the physical abilities of our sense organs and are interpreted according to our understanding of how the world works, which can be influenced by culture, experience, or education. According to science education specialist, George F. Kneller, "Surprising as it may seem, there is no fact that is not colored by our preconceptions" ("A Method of Enquiry," from Science and Its Ways of Knowing [Upper Saddle River: Prentice-Hall Inc., 1997], 15).

Observations made by a scientist are also limited by the sensitivity of whatever equipment he is using. Research findings will be limited at times by the available technology. For example, Italian physicist and philosopher Galileo Galilei (1564–1642) was reportedly the first person to observe the heavens with a telescope. Imagine how it must have felt to him to see the heavens through this amazing new instrument! It opened a window to the stars and planets and allowed new observations undreamed of before.

In the centuries since Galileo, increasingly more powerful telescopes have been devised that dwarf the power of that first device. In the past decade, we have marveled at images from deep space , courtesy of the Hubble Space Telescope, a large telescope that orbits Earth. Because of its view from outside the distorting effects of the atmosphere, the Hubble can look 50 times farther into space than the best earth-bound telescopes, and resolve details a tenth of the size (Seeds, Michael A., Horizons: Exploring the Universe , 5 th ed. [Belmont: Wadsworth Publishing Company, 1998], 86-87).

Construction is underway on a new radio telescope that scientists say will be able to detect electromagnetic waves from the very edges of the universe! This joint U.S.-Mexican project may allow us to ask questions about the origins of the universe and the beginnings of time that we could never have hoped to answer before. Completion of the new telescope is expected by the end of 2001.

Although the amount of detail observed by Galileo and today's astronomers is vastly different, the stars and their relationships have not changed very much. Yet with each technological advance, the level of detail of observation has been increased, and with it, the power to answer more and more challenging questions with greater precision.

Question: What are some of the differences between a casual observation and a 'scientific observation'?

Step 2: The Hypothesis

A hypothesis is a statement created by the researcher as a potential explanation for an observation or phenomena. The hypothesis converts the researcher's original question into a statement that can be used to make predictions about what should be observed if the hypothesis is true. For example, given the hypothesis, "exposure to ultraviolet (UV) radiation increases the risk of skin cancer," one would predict higher rates of skin cancer among people with greater UV exposure. These predictions could be tested by comparing skin cancer rates among individuals with varying amounts of UV exposure. Note how the hypothesis itself determines what experiments or further observations should be made to test its validity. Results of tests are then compared to predictions from the hypothesis, and conclusions are stated in terms of whether or not the data supports the hypothesis. So the hypothesis serves a guide to the full process of scientific inquiry.

The Qualities of a Good Hypothesis

• A hypothesis must be testable or provide predictions that are testable. It can potentially be shown to be false by further observations or experimentation.
• A hypothesis should be specific. If it is too general it cannot be tested, or tests will have so many variables that the results will be complicated and difficult to interpret. A well-written hypothesis is so specific it actually determines how the experiment should be set up.
• A hypothesis should not include any untested assumptions if they can be avoided. The hypothesis itself may be an assumption that is being tested, but it should be phrased in a way that does not include assumptions that are not tested in the experiment.
• It is okay (and sometimes a good idea) to develop more than one hypothesis to explain a set of observations. Competing hypotheses can often be tested side-by-side in the same experiment.

Question: Why is the hypothesis important to the scientific method?

Step 3: Testing the Hypothesis

A hypothesis may be tested in one of two ways: by making additional observations of a natural situation, or by setting up an experiment. In either case, the hypothesis is used to make predictions, and the observations or experimental data collected are examined to determine if they are consistent or inconsistent with those predictions. Hypothesis testing, especially through experimentation, is at the core of the scientific process. It is how scientists gain a better understanding of how things work.

Testing a Hypothesis by Observation

Some hypotheses may be tested through simple observation. For example, a researcher may formulate the hypothesis that the sun always rises in the east. What might an alternative hypothesis be? If his hypothesis is correct, he would predict that the sun will rise in the east tomorrow. He can easily test such a prediction by rising before dawn and going out to observe the sunrise. If the sun rises in the west, he will have disproved the hypothesis. He will have shown that it does not hold true in every situation. However, if he observes on that morning that the sun does in fact rise in the east, he has not proven the hypothesis. He has made a single observation that is consistent with, or supports, the hypothesis. As a scientist, to confidently state that the sun will always rise in the east, he will want to make many observations, under a variety of circumstances. Note that in this instance no manipulation of circumstance is required to test the hypothesis (i.e., you aren't altering the sun in any way).

Testing a Hypothesis by Experimentation

An experiment is a controlled series of observations designed to test a specific hypothesis. In an experiment, the researcher manipulates factors related to the hypothesis in such a way that the effect of these factors on the observations (data) can be readily measured and compared. Most experiments are an attempt to define a cause-and-effect relationship between two factors or events—to explain why something happens. For example, with the hypothesis "roses planted in sunny areas bloom earlier than those grown in shady areas," the experiment would be testing a cause-and-effect relationship between sunlight and time of blooming.

A major advantage of setting up an experiment versus making observations of what is already available is that it allows the researcher to control all the factors or events related to the hypothesis, so that the true cause of an event can be more easily isolated. In all cases, the hypothesis itself will determine the way the experiment will be set up. For example, suppose my hypothesis is "the weight of an object is proportional to the amount of time it takes to fall a certain distance." How would you test this hypothesis?

The Qualities of a Good Experiment

• The experiment must be conducted on a group of subjects that are narrowly defined and have certain aspects in common. This is the group to which any conclusions must later be confined. (Examples of possible subjects: female cancer patients over age 40, E. coli bacteria, red giant stars, the nicotine molecule and its derivatives.)
• All subjects of the experiment should be (ideally) completely alike in all ways except for the factor or factors that are being tested. Factors that are compared in scientific experiments are called variables. A variable is some aspect of a subject or event that may differ over time or from one group of subjects to another. For example, if a biologist wanted to test the effect of nitrogen on grass growth, he would apply different amounts of nitrogen fertilizer to several plots of grass. The grass in each of the plots should be as alike as possible so that any difference in growth could be attributed to the effect of the nitrogen. For example, all the grass should be of the same species, planted at the same time and at the same density, receive the same amount of water and sunlight, and so on. The variable in this case would be the amount of nitrogen applied to the plants. The researcher would not compare differing amounts of nitrogen across different grass species to determine the effect of nitrogen on grass growth. What is the problem with using different species of plants to compare the effect of nitrogen on plant growth? There are different kinds of variables in an experiment. A factor that the experimenter controls, and changes intentionally to determine if it has an effect, is called an independent variable . A factor that is recorded as data in the experiment, and which is compared across different groups of subjects, is called a dependent variable . In many cases, the value of the dependent variable will be influenced by the value of an independent variable. The goal of the experiment is to determine a cause-and-effect relationship between independent and dependent variables—in this case, an effect of nitrogen on plant growth. In the nitrogen/grass experiment, (1) which factor was the independent variable? (2) Which factor was the dependent variable?
• Nearly all types of experiments require a control group and an experimental group. The control group generally is not changed in any way, but remains in a "natural state," while the experimental group is modified in some way to examine the effect of the variable which of interest to the researcher. The control group provides a standard of comparison for the experimental groups. For example, in new drug trials, some patients are given a placebo while others are given doses of the drug being tested. The placebo serves as a control by showing the effect of no drug treatment on the patients. In research terminology, the experimental groups are often referred to as treatments , since each group is treated differently. In the experimental test of the effect of nitrogen on grass growth, what is the control group? In the example of the nitrogen experiment, what is the purpose of a control group?
• In research studies a great deal of emphasis is placed on repetition. It is essential that an experiment or study include enough subjects or enough observations for the researcher to make valid conclusions. The two main reasons why repetition is important in scientific studies are (1) variation among subjects or samples and (2) measurement error.

Variation among Subjects

There is a great deal of variation in nature. In a group of experimental subjects, much of this variation may have little to do with the variables being studied, but could still affect the outcome of the experiment in unpredicted ways. For example, in an experiment designed to test the effects of alcohol dose levels on reflex time in 18- to 22-year-old males, there would be significant variation among individual responses to various doses of alcohol. Some of this variation might be due to differences in genetic make-up, to varying levels of previous alcohol use, or any number of factors unknown to the researcher.

Because what the researcher wants to discover is average dose level effects for this group, he must run the test on a number of different subjects. Suppose he performed the test on only 10 individuals. Do you think the average response calculated would be the same as the average response of all 18- to 22-year-old males? What if he tests 100 individuals, or 1,000? Do you think the average he comes up with would be the same in each case? Chances are it would not be. So which average would you predict would be most representative of all 18- to 22-year-old males?

A basic rule of statistics is, the more observations you make, the closer the average of those observations will be to the average for the whole population you are interested in. This is because factors that vary among a population tend to occur most commonly in the middle range, and least commonly at the two extremes. Take human height for example. Although you may find a man who is 7 feet tall, or one who is 4 feet tall, most men will fall somewhere between 5 and 6 feet in height. The more men we measure to determine average male height, the less effect those uncommon extreme (tall or short) individuals will tend to impact the average. Thus, one reason why repetition is so important in experiments is that it helps to assure that the conclusions made will be valid not only for the individuals tested, but also for the greater population those individuals represent.

"The use of a sample (or subset) of a population, an event, or some other aspect of nature for an experimental group that is not large enough to be representative of the whole" is called sampling error (Starr, Cecie, Biology: Concepts and Applications , 4 th ed. [Pacific Cove: Brooks/Cole, 2000], glossary). If too few samples or subjects are used in an experiment, the researcher may draw incorrect conclusions about the population those samples or subjects represent.

Use the jellybean activity below to see a simple demonstration of samping error.

Directions: There are 400 jellybeans in the jar. If you could not see the jar and you initially chose 1 green jellybean from the jar, you might assume the jar only contains green jelly beans. The jar actually contains both green and black jellybeans. Use the "pick 1, 5, or 10" buttons to create your samples. For example, use the "pick" buttons now to create samples of 2, 13, and 27 jellybeans. After you take each sample, try to predict the ratio of green to black jellybeans in the jar. How does your prediction of the ratio of green to black jellybeans change as your sample changes?

Measurement Error

The second reason why repetition is necessary in research studies has to do with measurement error. Measurement error may be the fault of the researcher, a slight difference in measuring techniques among one or more technicians, or the result of limitations or glitches in measuring equipment. Even the most careful researcher or the best state-of-the-art equipment will make some mistakes in measuring or recording data. Another way of looking at this is to say that, in any study, some measurements will be more accurate than others will. If the researcher is conscientious and the equipment is good, the majority of measurements will be highly accurate, some will be somewhat inaccurate, and a few may be considerably inaccurate. In this case, the same reasoning used above also applies here: the more measurements taken, the less effect a few inaccurate measurements will have on the overall average.

Step 4: Data Analysis

In any experiment, observations are made, and often, measurements are taken. Measurements and observations recorded in an experiment are referred to as data . The data collected must relate to the hypothesis being tested. Any differences between experimental and control groups must be expressed in some way (often quantitatively) so that the groups may be compared. Graphs and charts are often used to visualize the data and to identify patterns and relationships among the variables.

Statistics is the branch of mathematics that deals with interpretation of data. Data analysis refers to statistical methods of determining whether any differences between the control group and experimental groups are too great to be attributed to chance alone. Although a discussion of statistical methods is beyond the scope of this tutorial, the data analysis step is crucial because it provides a somewhat standardized means for interpreting data. The statistical methods of data analysis used, and the results of those analyses, are always included in the publication of scientific research. This convention limits the subjective aspects of data interpretation and allows scientists to scrutinize the working methods of their peers.

Why is data analysis an important step in the scientific method?

Step 5: Stating Conclusions

The conclusions made in a scientific experiment are particularly important. Often, the conclusion is the only part of a study that gets communicated to the general public. As such, it must be a statement of reality, based upon the results of the experiment. To assure that this is the case, the conclusions made in an experiment must (1) relate back to the hypothesis being tested, (2) be limited to the population under study, and (3) be stated as probabilities.

The hypothesis that is being tested will be compared to the data collected in the experiment. If the experimental results contradict the hypothesis, it is rejected and further testing of that hypothesis under those conditions is not necessary. However, if the hypothesis is not shown to be wrong, that does not conclusively prove that it is right! In scientific terms, the hypothesis is said to be "supported by the data." Further testing will be done to see if the hypothesis is supported under a number of trials and under different conditions.

If the hypothesis holds up to extensive testing then the temptation is to claim that it is correct. However, keep in mind that the number of experiments and observations made will only represent a subset of all the situations in which the hypothesis may potentially be tested. In other words, experimental data will only show part of the picture. There is always the possibility that a further experiment may show the hypothesis to be wrong in some situations. Also, note that the limits of current knowledge and available technologies may prevent a researcher from devising an experiment that would disprove a particular hypothesis.

The researcher must be sure to limit his or her conclusions to apply only to the subjects tested in the study. If a particular species of fish is shown to consume their young 90 percent of the time when raised in captivity, that doesn't necessarily mean that all fish will do so, or that this fish's behavior would be the same in its native habitat.

Finally, the conclusions of the experiment are generally stated as probabilities. A careful scientist would never say, "drug x kills cancer cells;" she would more likely say, "drug x was shown to destroy 85 percent of cancerous skin cells in rats in lab trials." Notice how very different these two statements are. There is a tendency in the media and in the general public to gravitate toward the first statement. This makes a terrific headline and is also easy to interpret; it is absolute. Remember though, in science conclusions must be confined to the population under study; broad generalizations should be avoided. The second statement is sound science. There is data to back it up. Later studies may reveal a more universal effect of the drug on cancerous cells, or they may not. Most researchers would be unwilling to stake their reputations on the first statement.

As a student, you should read and interpret popular press articles about research studies very carefully. From the text, can you determine how the experiment was set up and what variables were measured? Are the observations and data collected appropriate to the hypothesis being tested? Are the conclusions supported by the data? Are the conclusions worded in a scientific context (as probability statements) or are they generalized for dramatic effect? In any researched-based assignment, it is a good idea to refer to the original publication of a study (usually found in professional journals) and to interpret the facts for yourself.

Qualities of a Good Experiment

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• all subjects treated alike except for the factor or variable being studied
• a control group is used for comparison
• measurements related to the factors being studied are carefully recorded
• enough samples or subjects are used so that conclusions are valid for the population of interest
• conclusions made relate back to the hypothesis, are limited to the population being studied, and are stated in terms of probabilities

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How to Write a Great Hypothesis

Hypothesis Definition, 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.

• Operationalization

Hypothesis Types

Hypotheses examples.

• Collecting Data

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. It is a preliminary answer to your question that helps guide the research process.

Consider a study designed to examine the relationship between sleep deprivation and test performance. The hypothesis might be: "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."

At a Glance

A hypothesis is crucial to scientific research because it offers a clear direction for what the researchers are looking to find. This allows them to design experiments to test their predictions and add to our scientific knowledge about the world. 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. At this point, researchers then 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 numerous 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 adage 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.

How to Formulate a Good Hypothesis

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.

The Importance of Operational Definitions

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.

Operational definitions are specific definitions for all relevant factors in a study. This process helps make vague or ambiguous concepts detailed and measurable.

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 various ways. Clearly defining these variables and how they are measured helps ensure that other researchers can replicate your results.

Replicability

One of the basic principles of any type of scientific research is that the results must be replicable.

Replication means repeating an experiment in the same way to produce the same results. 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. For example, 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.

To measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming others. The researcher might utilize a simulated task to measure aggressiveness in this situation.

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 there is a relationship between one independent variable and one dependent variable.
• Complex hypothesis : This type suggests a relationship between three or more variables, such as two independent and dependent variables.
• 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 population sample 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."
• "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."
• "Children who receive a new reading intervention will have higher reading scores than students who do not receive the intervention."

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:

• "There is no difference in anxiety levels between people who take St. John's wort supplements and those who do not."
• "There is no difference in scores on a memory recall task between children and adults."
• "There is no difference in aggression levels between children who play first-person shooter games and those who do not."

Examples of an alternative hypothesis:

• "People who take St. John's wort supplements will have less anxiety than those who do not."
• "Adults will perform better on a memory task than children."
• "Children who play first-person shooter games will show higher levels of aggression than children who do not." 

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  conducting an experiment is difficult or impossible. 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 examine how the variables are related. This 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.

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.

Thompson WH, Skau S. On the scope of scientific hypotheses .  R Soc Open Sci . 2023;10(8):230607. doi:10.1098/rsos.230607

Taran S, Adhikari NKJ, Fan E. Falsifiability in medicine: what clinicians can learn from Karl Popper [published correction appears in Intensive Care Med. 2021 Jun 17;:].  Intensive Care Med . 2021;47(9):1054-1056. doi:10.1007/s00134-021-06432-z

Eyler AA. Research Methods for Public Health . 1st ed. Springer Publishing Company; 2020. doi:10.1891/9780826182067.0004

Nosek BA, Errington TM. What is replication ?  PLoS Biol . 2020;18(3):e3000691. doi:10.1371/journal.pbio.3000691

Aggarwal R, Ranganathan P. Study designs: Part 2 - Descriptive studies .  Perspect Clin Res . 2019;10(1):34-36. doi:10.4103/picr.PICR_154_18

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."

Defining Research Questions and Hypotheses for Experiments

The foundation of a successful experimental study is a well-defined research question and a clear hypothesis. These elements serve as the central driving factors of the entire research process. They will inform how data is collected, the methods used to analyze it, and the lens through which results will be interpreted. Without clarity in a research question and hypothesis, researchers run the risk of conducting vague experiments that do not have applicable or correctly interpretable results.  

This article will explore how to define effective research questions, formulate relevant hypotheses, and avoid common errors made in the process.  

Understanding Research Questions

A research question is broadly defined as the central question an experiment seeks to answer. It must frame the scope and direction of the study and it will be used to influence all subsequent decisions made in the research process. The best research questions arise from an understanding of what is already known in the field and an awareness of unresolved issues or gaps in knowledge that can be filled with new experimental results.  

When developing a research question, it is critical that it be relevant to the overarching field of research. However, a research question but also be feasible given the available time, resources, and tools in order to lead to a successful experiment.  

Characteristics of a Strong Research Question

All strong research questions share a few key characteristics:  

• Clear and specific . The question should clearly outline what is being investigated and avoid vague terms that might confuse interpretation or application of the question.
• Researchable . The question must be answerable using existing scientific methods and not be so abstract that it is impossible to investigate empirically.
• Focused . The question should have a narrow focus so that it is controlled and manageable for a single experiment or set of related experiments.
• Significant . The question should contribute to the field by addressing an outstanding known issue or gap in knowledge.

For example, a weak research question may be “how does marketing impact sales” while a strong research question may be “how does the frequency of an email campaign impact monthly sales over a six month period?” The second question is much more specific and focused and the limited time frame makes it more researchable than the vague impact referenced in the first question.  

Going from Research Question to Hypothesis

Once you have a well-defined research question, the next step is to craft a hypothesis. This effectively translates the question into a statement that can be tested experimentally. The hypothesis will serve as the prediction that you will later provide support for or against using your experiment.  

There are two forms of a hypothesis. The null hypothesis suggests that there is no effect or relationship between the variables and is the default position you are hoping to disprove. For example, the null hypothesis could be that there is no difference in monthly sales over a six month period when email campaigns are implemented. The alternative hypothesis suggests a specific relationship between the variables based on what the researcher expects to see in the data. For example, an alternative hypothesis could be that an increase of three marketing emails a month will be associated with a 10% increase in monthly sales over a six month period.  

Characteristics of a Strong Hypothesis

A strong hypothesis must have these three characteristics:  

• Testable . The hypothesis must refer to an outcome that can be measured and assessed in the experiment.
• Falsifiable . The hypothesis must be able to be refuted through experimentation. If it is impossible to disprove, it cannot be a valid hypothesis.
• Specific . The hypothesis should predict a specific effect or relationship and not refer to a general trend.

For example, a hypothesis that emails will increase sales is not specific enough to be a valid hypothesis because it does not indicate the magnitude of emails or increase in sales that would be necessary to support the hypothesis.  

Iterative Refining

The process of defining research questions and hypotheses is often iterative. As you better understand the field, literature, and get feedback from subject experts, your questions and hypotheses can change.Be open to revising these elements as new information arises as scientific inquiry is often a dynamic, changing process.  

A tool that is commonly used to validate research questions and hypotheses is small-scale pilot studies. These involve collecting small data sets and conducting brief preliminary analysis to determine the feasibility of your questions and hypothesis. Pilot studies can also reveal unanticipated issues with the question, hypothesis, or research design that can be addressed before a large-scale experiment is started.  

Defining strong research questions and hypotheses is an essential first step in any experiment as these elements shape the focus, direction, and success of your study. In the process, it is important to ensure that these elements are specific, measurable, and relevant to the overall field. A well-defined research question and hypothesis are not just formalities; they are the pillars of a successful and scientifically sound experiment.  

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Mehrnaz holds a Masters in Data Analytics and is a full time biostatistician working on complex machine learning development and statistical analysis in healthcare. She has experience with AI and has taught university courses in biostatistics and machine learning at University of the People.

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What Are Examples of a Hypothesis?

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

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

Hypotheses Examples: Null

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

Hypotheses Examples: If, Then

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

Improving a Hypothesis to Make It Testable

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

Eating greasy food causes pimples.

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

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

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

Getting pimples is unaffected by eating greasy food.

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

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

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