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Associate Professor of Teaching/Instruction Temple University Marcia Bailey "Hypothesis is an excellent tool to engage students with the text and with each other. I used it almost weekly this semester."
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EDUR 7130 Educational Research On-Line

A hypothesis is, very simply, a guess one makes about what will happen. For example, if one were asked to predict which students would obtain higher achievement scores on a test, a group who used cooperative learning or a group who received lecture-only, most would guess--hypothesize--that the cooperative learning group would obtain the higher achievement scores.

In most research situations, a hypothesis represents an educated, an informed, guess. Often the hypothesis is based on theory or logic; sometimes it is based on prior experience or data. When formulating a hypothesis, there are characteristics that will make it reasonable and acceptable to most readers.

  • Consistent with previous research : Hypotheses that contradict previous research, especially a large body of research, must have sound reasoning in order for it to be acceptable by the reader. For example, it would seem odd, using the example above, to hypothesize that the lecture group would have higher achievement scores given that much of the research on cooperative learning supports the notion that cooperative learning results in better student achievement.
  • Clearly and concisely stated : No need to elaborate on this.
  • Testable : To be testable means that the hypothesis can be addressed by collecting and analyzing data; that is, data can be used to determine whether the hypothesis is or is not supported. If one's hypothesis cannot be addressed by collecting data, then it is not testable.
  • Variables : Like problem statements , the important variables to be studied should be presented in the hypotheses.
  • Relationships : Also similar to problem statements, relationships among the variables studied should be clear--that is, one should be able to identify which are the independent and dependent variables in the hypothesis.
  • Placement : Normally it is best to introduce the reader to the logic and history of the problem to be studied before introducing the hypotheses, so this suggests that hypotheses should come after the literature review and just prior to the methods section.

Type of Hypotheses

Hypotheses may be either directional, non-directional, or null. The specific wording of the hypothesis will depend upon whether the independent variable in question is qualitative or quantitative. In general, if the independent variable is qualitative, the hypothesis refers to group differences. For example, there will be differences between boys and girls in reading achievement. If the independent variable is quantitative, the hypothesis is written in the format of relationships among variables rather than group differences. For example, reading achievement is related to verbal recall ability. Specific differences among directional, non-directional, and null hypotheses are presented below, but first it is necessary to explain the types of relationships one may find among quantitative variables.

When one wishes to express the nature of the relationship between two quantitative variables, there several possible variations on types of relationships. In most cases, at least in education and the social sciences, relationships among quantitative variables will follow either a positive, negative (inverse), or no relationship pattern. Others are possible (e.g., non-linear relationships).

A positive relationship exists when two variables covary together in a similar manner; that is, when increases in one variable are associated with increases in another variable. So, in simpler terms, when one variable goes up , the other variable also goes up . For example, people with high levels of intelligence are expected to have higher grades in school; those with higher levels of motivation complete more work; the more publications a professor has in a given year, the higher the merit pay for that year.

A negative relationship represents two variables that covary in opposite directions. Thus, when one variable increases , the other variable decreases . A negative relationship is also referred to as an inverse relationship. Two examples of inverse relationships are: the greater one's belief in one's ability to learn, the lower one's anxiety about a course; the more associated one feels with school, the less likely one will drop out of school.

Below is a matrix that identifies the type of hypothesis by the type of independent variable. More detailed descriptions of each type follow the matrix.

Matrix of Hypotheses (Assuming the dependent variable is quantitative.)

A directional hypothesis indicates that one expects a group to over- or under-perform relative to other groups, or for there to be a positive or negative relationship among variables. To know when to refer to group differences or relationships among variables, it is necessary to know whether the independent variable is qualitative or quantitative. As noted above, if the independent variable is qualitative, the hypothesis is written in a manner that indicates one group's superior (or inferior) performance. If the independent variable is quantitative, reference in the hypothesis is to positive or negative relationships among variables.

To illustrate a directional hypothesis, the following indicates that one group will perform better in achievement that another. Note that the independent variable is qualitative.

Directional Hypothesis 1 : Students exposed to cooperative learning will score higher on an achievement test that students exposed to lecture.

The following directional hypothesis indicates a positive relationship among the variables. Note that the independent variable is qualitative.

Directional Hypothesis 2 : Students with higher levels of intelligence will score higher on tests designed to measure mental abilities. (The higher the intelligence, the better the test score.)

The following directional hypothesis indicates a negative relationship among the variables. Note that the independent variable is quantitative.

Directional Hypothesis 3 : Students with higher levels of test anxiety will score lower on an achievement test. (So, as anxiety increases, performance decreases.)

For qualitative independent variables, a non-directional hypothesis indicates that groups will differ, but does not specify which groups will be superior or inferior. For quantitative independent variables, the non-directional hypothesis simply indicates that a relationship exists, but does not specifies the nature (positive or negative) of the relationship.

Non-directional Hypothesis 1 : There will be a difference in achievement between students exposed to cooperative learning and students exposed to lecture.

Note that for non-directional hypotheses with qualitative independent variables, it is important to specify that one expects a difference among the groups. This manner of writing non-directional hypotheses with qualitative independent variables is preferred over simply stating that the variables are related. But for non-directional hypotheses with quantitative independent variables, indicating that an association or relationship is expected is acceptable, as illustrated below.

Non-Directional Hypothesis 2 : There is a relationship between a student's level of intelligence and his or her score on a test designed to measure mental abilities.

For null hypotheses, one simply indicates that there will be no difference (for qualitative independent variables) or that no relationship exists (for quantitative independent variables).

Null Hypothesis 1 : There will be a no difference in achievement between students exposed to cooperative learning and students exposed to lecture.

Null Hypothesis 2 : The is no relationship between a student's level of intelligence and his or her score on a test designed to measure mental abilities.

Sometimes one may read of a research hypothesis. A research hypothesis is nothing more than one the researcher expects to find in his or her study. Also, one may occasionally see reference to a statistical hypothesis. A statistical hypothesis is simply a null hypothesis.

Practice Exercise

  • the independent (IV) and dependent (DV) variables;
  • indicate if IV is qualitative or quantitative, and if qualitative, indicate the categories of the IV;
  • whether the hypothesis is directional, non-directional, or null;
  • and for directional hypotheses, specify which group is expected to do better or whether a positive or negative relationship is expected.

Illustrated Example 1 :

  • IV is research experience, DV is achievement (the DV is not greater achievement)
  • IV is qualitative since there are two groups, and the two groups are (1) those with research experience and (2) those without research experience
  • hypothesis is directional (specifies that one group will do better than the other group—those with research experience will do better)
  • IV has categories (i.e., groups), and those with research experience are expected to have greater achievement.

Illustrated Example 2 :

  • IV is amount of studying, DV is performance on achievement tests
  • IV is quantitative (amount of studying can be ranked from more to less)
  • hypothesis is directional
  • positive relationship is expected--as studying increases, so does achievement
  • Children taught by the vocabulary method will learn more than children taught by the experimental method.
  • The greater one's retention ability, the more one’s learning from related prose will increase.
  • Given equal prior learning, corrective and non-corrective instruction are likely to produce different levels of achievement among fourth-grade students.
  • Programs offering stipends will be just as successful at retaining students as programs not offering stipends.
  • In a middle-class, suburban, public school district in which a child is expected to meet the standards of a set curriculum, a child who is under five years of age upon entrance to kindergarten is less likely to be ready for first grade in one year than a child who is five years of age or more at the time of entrance to kindergarten.
  • Fourth grade students who participate in computer assisted instruction (CAI) will have higher mathematics achievement scores than fourth grade students who do not participate in CAI.
  • Teachers who establish rapport with their students will be more effective in motivating students to study than teachers who do not establish rapport with their students.
  • Students with higher SAT scores will also have higher GRE scores; similarly, students with lower SAT scores will have lower GRE scores.
  • Under intangible reinforcement conditions, middle-class children will learn more than lower-class children.
  • The average achievement group and the low achievement group will show the same level in ratings of self-worth.
  • Classroom intellectual composition was expected to directly influence students’ academic achievement; the higher the classroom intellectual composition, the greater the academic achievement.
  • There will be no difference in mathematics achievement between the computer and tutor group, the computer-only group, and the traditional instruction group.
  • Students’ confidence in their academic ability and their intelligence are both related to achievement.
  • Test-taking experience affects test performance.
  • Students who receive individually guided instruction will demonstrate greater gains in reading achievement than students who receive group based instruction.
  • Students exposed to the read, visualize, and draw condition are expected to comprehend more of the biology text than are students in the read and visualize condition or the read only condition.
  • Science achievement is independent of academic self-efficacy.
  • Perceptions of the characteristics of the "good" or effective teacher are in part determined by the perceiver’s attitudes toward education.
  • Academic performance in school is related to dropping out of school.
  • Perceived autonomy in the classroom predicts student evaluations of instruction. (Note: Perceived autonomy is measured by several responses to Likert scaled items. Reposes to each item range from 1 "strongly disagree" to 5 "strongly agree.")

Practice Exercise Answers

  • I V is method of instruction, DV is amount learned
  • qualitative, categories are vocabulary and experimental
  • directional
  • vocabulary learns more
  • IV is retention ability, DV is amount learned
  • IV is quantitative (retention ability ranges from high to low, so it is quantitative)
  • positive relationship
  • IV is type of instruction, DV is achievement (note, prior learning and fourth-graders are not variables, they do not vary since everyone referred to in the hypothesis has prior learning and is a fourth grader, therefore these two are constants)
  • qualitative, categories are corrective and non-corrective
  • non-directional
  • not applicable (n/a)
  • IV is whether stipends are offered, DV is retention of students
  • qualitative, stipends offered vs. not offered
  • null -- no difference in retention between the two types of programs
  • IV age of child, DV is readiness for first grade
  • qualitative, two categories, under 5 vs. 5 or over (if you argue that age is quantitative you are technically correct since these categories can be ranked, but since there are only two categories, I treat age as a qualitative variable)
  • 5 or over more ready
  • IV is participation in CAI, DV is mathematics achievement (fourth grade and student are not variables, they are constants)
  • qualitative, two categories, use CAI and not use CAI
  • those who use CAI have higher scores
  • IV is establishment of rapport, DV is motivation to study
  • qualitative, two categories, those who establish rapport and those who do not
  • teachers who establish rapport better at motivating students
  • IV is SAT, DV is GRE (if you are not familiar with SAT and GRE, then you will not be able to identify which is IV and DV; usually SAT is a test taken in high school, GRE is taken in college, therefore SAT precedes GRE in chronological order)
  • IV is quantitative, scores from SAT can be ranked from high to low
  • positive relationship; as scores from SAT increase, so too do scores from GRE
  • IV is class status, DV is learning (intangible reinforcement conditions is a constant, all of these children are under this situation; children are not a variable since all participants in the hypothesis are children)
  • qualitative, categories are middle and lower (if you thought this was a quantitative variable, you would also be correct since class status can be ranked, but I identify it as qualitative since there are only two categories)
  • middle-class learn more
  • IV is achievement group, DV is self-worth
  • qualitative, categories are average and low (if you thought this was a quantitative variable, you would also be correct since average level and low level can be ranked, but I identify it as qualitative since there are only two categories)
  • IV is intellectual composition, DV academic achievement
  • quantitative, intellectual composition varies and can be ranked (note, the higher--er--signifies comparative form of the word and therefore represents degrees of quality or amount, hence intellectual composition varies by degree so is quantitative)
  • positive, the great intellectual composition, the greater the learning
  • IV is type of instruction (group), DV is mathematics achievement
  • qualitative, categories are tutor, computer-only, and traditional instruction
  • IVs are confidence in academic ability, and intelligence, DV is achievement
  • both confidence and intelligence are quantitative (most likely), since they both vary by degree (can be ranked from high to low)
  • non-directional, no specific positive or negative relationship identified
  • IV is experience, DV is performance
  • quantitative, experience can be ranked from more to less
  • non-directional, the exact relationship is not specified
  • IV type of instruction, DV reading achievement
  • qualitative, guided and group
  • guided will do better in reading
  • IV is type of condition, DV is comprehension
  • qualitative, with three categories, (a) read, visualize, and draw, (b) read and visualize, and (c) read
  • those using read, visualize, and draw comprehend more
  • IV academic self-efficacy, DV is science achievement; this one may be confusing for some. One way to identify the IV and DV is to read the hypothesis again, but to change the word INdependent to DEPENDENT, so:  "Science achievement is dependent upon academic self-efficacy." In this sentence it should be clear that achievement is dependent on self-efficacy. Whenever it is stated that variable A is independent of variable B, then variable A is the dependent variable.
  • quantitative, self-efficacy may be ranked from high to low
  • null, stating that one variable is independent of another indicates no relationship between the two
  • IV is attitude, DV is perception
  • difficult to determine whether attitude is qualitative or quantitative without more information about how this variable was defined and measured
  • IV is academic performance, DV is dropping out
  • quantitative
  • IV is perceived autonomy, DV is student ratings of instruction


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100 Hypothesis Examples Across Various Academic Fields

David Costello

A hypothesis is a statement or proposition that is made for the purpose of testing through empirical research. It represents an educated guess or prediction that can be tested through observation and experimentation. A hypothesis is often formulated using a logical construct of "if-then" statements, allowing researchers to set up experiments to determine its validity. It serves as the foundation of a scientific inquiry, providing a clear focus and direction for the study. In essence, a hypothesis is a provisional answer to a research question , which is then subjected to rigorous testing to determine its accuracy.

In this blog post, we'll explore 100 different hypothesis examples, showing you how these simple statements set the stage for discovery in various academic fields. From the mysteries of chemical reactions to the complexities of human behavior, hypotheses are used to kickstart research in numerous disciplines. Whether you're new to the world of academia or just curious about how ideas are tested, these examples will offer insight into the fundamental role hypotheses play in learning and exploration.

  • If a plant is given more sunlight, then it will grow faster.
  • If an animal's environment is altered, then its behavior will change.
  • If a cell is exposed to a toxin, then its function will be impaired.
  • If a species is introduced to a new ecosystem, then it may become invasive.
  • If an antibiotic is applied to a bacterial culture, then growth will be inhibited.
  • If a gene is mutated, then the corresponding protein may become nonfunctional.
  • If a pond's water temperature rises, then the algae population will increase.
  • If a bird species' habitat is destroyed, then its population will decrease.
  • If a mammal is given a high-fat diet, then its cholesterol levels will rise.
  • If human stem cells are treated with specific factors, then they will differentiate into targeted cell types.
  • If the concentration of a reactant is increased, then the rate of reaction will increase.
  • If a metal is placed in a solution of a salt of a less reactive metal, then a displacement reaction will occur.
  • If a solution's pH is lowered, then the concentration of hydrogen ions will increase.
  • If a gas is cooled at constant pressure, then its volume will decrease according to Charles's law.
  • If an endothermic reaction is heated, then the equilibrium position will shift to favor the products.
  • If an enzyme is added to a reaction, then the reaction rate will increase due to the lower activation energy.
  • If the pressure on a gas is increased at constant temperature, then the volume will decrease according to Boyle's law.
  • If a non-polar molecule is added to water, then it will not dissolve due to water's polarity.
  • If a piece of litmus paper is placed in a basic solution, then the color of the paper will turn blue.
  • If an electric current is passed through a salt solution, then the solution will undergo electrolysis and break down into its components.

Computer science

  • If a new algorithm is applied to a sorting problem, then the computational complexity will decrease.
  • If multi-factor authentication is implemented, then the security of a system will increase.
  • If a machine learning model is trained with more diverse data, then its predictive accuracy will improve.
  • If the bandwidth of a network is increased, then the data transmission rate will be faster.
  • If a user interface is redesigned following usability guidelines, then user satisfaction and efficiency will increase.
  • If a specific optimization technique is applied to a database query, then the retrieval time will be reduced.
  • If a new cooling system is used in a data center, then energy consumption will decrease.
  • If parallel processing is implemented in a computational task, then the processing time will be reduced.
  • If a software development team adopts Agile methodologies, then the project delivery time will be shortened.
  • If a more advanced error correction code is used in data transmission, then the error rate will decrease.
  • If the interest rate is lowered, then consumer spending will increase.
  • If the minimum wage is raised, then unemployment may increase among low-skilled workers.
  • If government spending is increased, then the Gross Domestic Product (GDP) may grow.
  • If taxes on luxury goods are raised, then consumption of those goods may decrease.
  • If a country's currency is devalued, then its exports will become more competitive.
  • If inflation is high, then the central bank may increase interest rates to control it.
  • If consumer confidence is high, then spending in the economy will likely increase.
  • If barriers to entry in a market are reduced, then competition will likely increase.
  • If a firm engages in monopolistic practices, then consumer welfare may decrease.
  • If unemployment benefits are extended, then the unemployment rate may be temporarily affected.
  • If class sizes are reduced, then individual student performance may improve.
  • If teachers receive ongoing professional development, then teaching quality will increase.
  • If schools implement a comprehensive literacy program, then reading levels among students will rise.
  • If parents are actively involved in their children's education, then students' academic achievement may increase.
  • If schools provide more access to extracurricular activities, then student engagement and retention may improve.
  • If educational technology is integrated into the classroom, then learning outcomes may enhance.
  • If a school adopts a zero-tolerance policy on bullying, then the incidence of bullying will decrease.
  • If schools provide nutritious meals, then student concentration and performance may improve.
  • If a curriculum is designed to include diverse cultural perspectives, then student understanding of different cultures will increase.
  • If schools implement individualized learning plans, then students with special needs will achieve better educational outcomes.

Environmental science

  • If deforestation rates continue to rise, then biodiversity in the area will decrease.
  • If carbon dioxide emissions are reduced, then the rate of global warming may decrease.
  • If a water body is polluted with nutrients, then algal blooms may occur, leading to eutrophication.
  • If renewable energy sources are used more extensively, then dependency on fossil fuels will decrease.
  • If urban areas implement green spaces, then the urban heat island effect may be reduced.
  • If protective measures are not implemented, then endangered species may become extinct.
  • If waste recycling practices are increased, then landfill usage and waste pollution may decrease.
  • If air quality regulations are enforced, then respiratory health issues in the population may decrease.
  • If soil erosion control measures are not implemented, then agricultural land fertility may decrease.
  • If ocean temperatures continue to rise, then coral reefs may experience more frequent bleaching events.
  • If a new chemotherapy drug is administered to cancer patients, then tumor size will decrease more effectively.
  • If a specific exercise regimen is followed by osteoarthritis patients, then joint mobility will improve.
  • If a population is exposed to higher levels of air pollution, then respiratory diseases such as asthma will increase.
  • If a novel surgical technique is utilized in cardiac surgery, then patient recovery times will be shortened.
  • If a targeted screening program is implemented for a specific genetic disorder, then early detection and intervention rates will increase.
  • If a community's water supply is fortified with fluoride, then dental cavity rates in children will decrease.
  • If an improved vaccination schedule is followed in a pediatric population, then the incidence of preventable childhood diseases will decline.
  • If nutritional supplements are provided to malnourished individuals, then general health and immune function will improve.
  • If stricter infection control protocols are implemented in hospitals, then the rate of hospital-acquired infections will decrease.
  • If organ transplant recipients are given a new immunosuppressant drug, then organ rejection rates will decrease.
  • If a person is exposed to violent media, then their aggression levels may increase.
  • If a child is given positive reinforcement, then desired behaviors will be more likely to be repeated.
  • If an individual suffers from anxiety, then their performance on tasks under pressure may decrease.
  • If a patient is treated with cognitive-behavioral therapy, then symptoms of depression may reduce.
  • If a person lacks sleep, then their cognitive functions and decision-making abilities will decline.
  • If an individual's self-esteem is increased, then their overall life satisfaction may improve.
  • If a person is exposed to a traumatic event, then they may develop symptoms of PTSD.
  • If social support is provided to an individual, then their ability to cope with stress will improve.
  • If a group works collaboratively, then they may exhibit improved problem-solving abilities.
  • If an individual is given autonomy in their work, then their job satisfaction and motivation will increase.
  • If the velocity of an object is increased, then the kinetic energy will also increase.
  • If the temperature of a gas is increased at constant pressure, then the volume will increase.
  • If the mass of an object is doubled, then the gravitational force it exerts will also double.
  • If the frequency of a wave is increased, then the energy it carries will increase.
  • If a magnet's distance from a metal object is decreased, then the magnetic force will increase.
  • If the angle of incidence equals the angle of reflection, then the law of reflection holds true.
  • If the resistance in an electrical circuit is increased, then the current will decrease.
  • If the force applied to a spring is doubled, then the extension of the spring will also double.
  • If a mirror is concave, then it will focus parallel rays to a point.
  • If a body is in uniform circular motion, then the net force toward the center is providing the centripetal acceleration.
  • If educational opportunities are equally distributed in a society, then social mobility will increase.
  • If community policing strategies are implemented, then trust between law enforcement and the community may improve.
  • If social media usage increases among teenagers, then face-to-face social interaction may decrease.
  • If gender wage gap policies are enforced, then disparities in earnings between men and women will decrease.
  • If a society emphasizes individualistic values, then community engagement and collective responsibility may decline.
  • If affordable housing initiatives are implemented in urban areas, then homelessness rates may decrease.
  • If a minority group is represented in media, then stereotypes and prejudices toward that group may decrease.
  • If a culture promotes work-life balance, then overall life satisfaction among its citizens may increase.
  • If increased funding is provided to community centers in underserved neighborhoods, then social cohesion and community engagement may improve.
  • If legislation is passed to protect the rights of LGBTQ+ individuals, then discrimination and stigma may decrease in society.

In the exploration of various academic disciplines, hypotheses play a crucial role as foundational statements that guide research and inquiry. From understanding complex biological processes to navigating the nuances of human behavior in sociology, hypotheses serve as testable predictions that shape the direction of scientific investigation. The examples provided across the fields of medicine, computer science, sociology, and education illustrate the diverse applications and importance of hypotheses in shaping our understanding of the world. Whether improving medical treatments, enhancing technological systems, fostering social equality, or elevating educational practices, hypotheses remain central to scientific progress and societal advancement. By formulating clear and measurable hypotheses, researchers can continue to unravel complex phenomena, contribute to their fields, and ultimately enrich human knowledge and well-being.

Header image by Qunica .

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15 Hypothesis Examples

hypothesis definition and example, explained below

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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Hypothesis in educational research

hypothesis examples about education

Hypothesis is one of the most essential elements in educational research in which variable based numeric data are collected and analysed. So, meaning, type, importance and characteristics of a good hypothesis are discussed here.


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  • 2. Content • Meaning of Hypothesis • Characteristics of Good Hypothesis • Importance of Hypothesis • Types of Hypothesis
  • 3. Meaning of Hypothesis Hypothesis is an assumption that is still not proved but shows the probable solution of the problem or predicts the relationship between two or more variables. The assumption is proved true or false by testing it. We will not have the solution to the problem until the assumption is tested. Three points, regarding such assumptions, are very important. • The assumptions are made on the basis of previous experiences or primary evidences or by thinking logically. • Whether the assumptions are true or false is decided by testing them. • Testing of assumptions lead to the solution of the problem. Thus, the hypothesis is a result of matured and logical thinking process.
  • 4. What does Hypothesis Testing Do? • By testing the hypothesis, some fact is established or some theory, rule or principle is formed or generalisation is done in the context of solution of the problem. • Hence, hypothetical statement is not an established fact or principle but by testing it the fact is derived or the solution is generalised. Click here to go to content
  • 5. Characteristics of a Good Hypothesis • A good hypothesis never opposes the universal truth and natural law and rules. • It is written in simple and easy language. • Only one assumption is made in one hypothesis. • The hypothesis is written in such a language that, after testing, it can be clearly rejected or not rejected. • Hypothesis is written in present tense because it is not a prediction or opinion but it is an assumption that is based on present factual information. Continue…….
  • 6. Characteristics of a Good Hypothesis …………Continue • A good hypothesis assures that the tool required for testing it (hypo) is available or can be prepared (developed) easily. • Before formulating the hypothesis, it is assured that the data will be available for testing it. • A good hypothesis assures that the entire process related to data collection, data analysis and testing the hypothesis is under the control of the researcher. Continue…….
  • 7. Characteristics of a Good Hypothesis …………Continue • It can be tested with the help of evidences and data. • If a testing of hypothesis gives a solution of main problem of research, it will be considered as a good hypothesis. • A good hypothesis gives the clear idea about the area of research, variable and statistical technique to be used for data analysis. • Generally, a hypothesis shows the relationship between two or more variables. Continue…….
  • 8. Characteristics of a Good Hypothesis …………Continue • Hypothesis is formulated before collecting and analysing the data. • Hypothesis is formulated by thinking logically. • Hypothesis is formulated on the basis of available primary evidences. • If experimental research is there, a hypothesis is formulated before conducting experiment. • A good hypothesis promotes deductive reasoning.
  • 9. Importance of a Hypothesis • It assumes the result of the research. Researcher collects data to test this assumption. • It specifies the type of data to be collected and prevents the researcher from collecting unnecessary data. • It helps the researcher to work in certain direction. • It helps in deriving clear findings of the research. • It gives the idea about the area and variables of the study and statistical technique to be applied for data analysis. Continue…….
  • 10. Importance of a Hypothesis …………Continue • It gives the idea about the structure of writing the findings in research report. • It inspires the researcher to do deductive reasoning. (In common term we can say that the thinking that is done to search the evidences to prove the established theory, principle or rule is called deductive reasoning.)
  • 11. Types of Hypothesis Main three types of Hypothesis are there as follows 1. Declarative / Alternate / Research Hypothesis 2. Question Type Hypothesis 3. Null Hypothesis
  • 12. Declarative / Alternate / Research Hypothesis Meaning: If a researcher formulates the hypothesis by keeping in mind some expected result, it is called declarative hypothesis. It is known as alternate or research hypothesis also. Researcher expects some result on the basis of his experience in the field or on the basis of the review or study of the literature. He converts such expectation in the hypothesis. It means, he makes some declaration about the result of the research. That is why such hypothesis is called declarative hypothesis. Declarative hypotheses are denoted by H1, H2, H3………..Hn
  • 13. Special Features of Declarative / Alternate / Research Hypothesis • Researcher formulates the declarative hypotheses on the basis of pre-experience, study of research material or on the basis of the findings of previous researches. • Such hypotheses are formulated on the basis of expected findings of the research. • Such hypothesis is accepted when null hypothesis is rejected. • Such hypothesis is influenced by the beliefs of the researcher. Therefore it cannot remain unbiased always. • There are two types of declarative hypothesis. 1. Directional and 2. Non-directional.
  • 14. Types of Declarative / Alternate / Research Hypothesis Main Two types of Declarative Hypothesis are there as follows 1. Directional Hypothesis 2. Non-directional Hypothesis
  • 15. Directional Hypothesis This hypothesis shows the expected direction of results. It means such hypothesis assumes a particular result in favour of some factor / variable. In other words it can be said that directional hypothesis expects particular result in favour of a certain variable out of the probable results. Examples • The teaching aptitude of the male student-teachers is better than that of female student- teachers. • There is a positive correlation between emotional maturity level and adjustment level of the female teachers of secondary schools.
  • 16. Non-Directional Hypothesis The hypothesis, which does not indicate the direction of the result or in which the result is not expected in favour of certain variable is called non- directional hypothesis. More clearly, it can be said that it assumes the difference but does not favour any variable in terms of dependent variable. In inter-relational studies, it assumes the relationship between variables but does not clarify the type of relationship like positive or negative. Examples • There is difference between teaching competency of male and female teachers of higher secondary schools. • There is a positive correlation between emotional maturity level and adjustment level of the female teachers of secondary schools.
  • 17. Question Type Hypothesis In this type of hypothesis, instead of expecting a certain result, a questions is formed. Examples • Is there difference between exam anxiety of arts, commerce and science students of higher secondary schools? • Is the exam anxiety of commerce students of higher secondary schools more than that of science students? • Is there positive correlation between intelligence and mental stress of government employees?
  • 18. Null Hypothesis If, in the context of dependent variable, the hypothesis indicates ‘no difference’ between two or more levels of independent variable, it is called null hypothesis. Null hypothesis indicates no relationship between two variables, if correlational study is there. Null hypothesis is indicated by the symbol HO. Such hypothesis is also called ‘no difference’ type of hypothesis or ‘no relation’ type of hypothesis. Null hypotheses are denoted as 𝑯 𝑶 𝟏 , 𝑯 𝑶 𝟐 , 𝑯 𝑶 𝟑 ………..𝑯 𝑶 𝒏 . Continue…….
  • 19. Null Hypothesis ……… Continue Example: • There is no significant effect of instructional method on the achievement of the students of grade nine in English. • There is no significant correlation between the scores of the students of secondary schools in mental health scale and reasoning ability test.
  • 20. Reference Shukla, Satishprakash, (2018) Research Methodology and Statistics, Ahmedabad: SSS Publications PROF. SATISHPRAKASH S. SHUKLA DEPARTMENT OF EDUCATION, GUJARAT UNIVERSITY, NAVRANGPURA, AHMEDABAD – 380009 E-MAIL: [email protected]

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  • How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples

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

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

Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

Table of contents

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

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

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

Variables in hypotheses

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

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

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

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

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Step 1. ask a question.

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

Step 2. Do some preliminary research

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

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

Step 3. Formulate your hypothesis

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

4. Refine your hypothesis

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

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

5. Phrase your hypothesis in three ways

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

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

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

6. Write a null hypothesis

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

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

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

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


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

Research bias

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

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

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

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

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How to Write a Great Hypothesis

Hypothesis Format, Examples, and Tips

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

hypothesis examples about education

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.

hypothesis examples about education

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  • The Scientific Method

Hypothesis Format

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

  • Collecting Data

Frequently Asked Questions

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

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

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

The Hypothesis in the Scientific Method

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

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

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

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

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

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

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

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

Elements of a Good Hypothesis

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

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

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

To form a hypothesis, you should take these steps:

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

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

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

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

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

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

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

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

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

Hypothesis Checklist

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

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

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

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

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

A few examples of simple hypotheses:

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

Examples of a complex hypothesis include:

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

Examples of a null hypothesis include:

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

Examples of an alternative hypothesis:

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

Collecting Data on Your Hypothesis

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

Descriptive Research Methods

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

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

Experimental Research Methods

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

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

A Word From Verywell

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

Some examples of how to write a hypothesis include:

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

The four parts of a hypothesis are:

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

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

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

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

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10 learning hypothesis – Activity 8 H817

Hand holding AT symbol

Rough notes

Very little academic literature on the theory of eLearning. It tends to be pragmatic and based on experience. Surprising considering the volume of literature on the subject.

What is a theory? “A theory can be described as a set of hypotheses that apply to all instances of a particular phenomenon, assisting in decision-making, philosophy of practice and effective implementation through practice”  interestingly……. “Theory can only be effectively communicated if a common set of terms is used and if their meaning is popularly adhered to”

Terms defined: Online learning, eLearning, learning Object, LMS, Interactive, pedagogy and Mixed-mode/blended/resource-based learning

Ten hypothesis for learning: (Direct from the article)

  • eLearning is a means of implementing education that can be applied within varying education models (for example, face to face or distance education) and educational philosophies (for example behaviourism and constructivism).
  • eLearning enables unique forms of education that fits within the existing paradigms of face to face and distance education.
  • The choice of eLearning tools should reflect rather than determine the pedagogy of a course; how technology is used is more important than which technology is used.
  • eLearning advances primarily through the successful implementation of pedagogical innovation.
  • eLearning can be used in two major ways; the presentation of education content, and the facilitation of education processes.
  • eLearning tools are best made to operate within a carefully selected and optimally integrated course design model.
  • eLearning tools and techniques should be used only after consideration has been given to online vs offline trade-offs.
  • Effective eLearning practice considers the ways in which end-users will engage with the learning opportunities provided to them.
  • The overall aim of education, that is, the development of the learner in the context of a predetermined curriculum or set of learning objectives, does not change when eLearning is applied.
  • Only pedagogical advantages will provide a lasting rationale for implementing eLearning approaches.

In order to eLearning to develop the theoretical underpinnings must be made explicit and available for critique. Ravenscroft (2001:150)   “given that the pace of change of educational technology is unlikely to slow down, the need for relatively more stable and theoretically founded interaction models is becoming increasingly important.”

Activity questions

Q1 – with which hypotheses do you agree.

As there is no one confined way of using eLearning, it fits into a broad array of forms and can be adapted into various educational philosophies. An example is   Second Life , its use a platform for learning fits many different ways of creating learning and engaging with students: From one on one conversations, presentations, simulations, group discussions and activities. It hosts regular “ inworld ” conferences to innovate in eLearning. The next one being March 9th to 12th 2016 if you fancy popping along.

Second life education conference

Image from page promoting Second Life Education Conference

2.  eLearning enables unique forms of education that fits within the existing paradigms of face to face and distance education.

Similar to the previous point, learning is not binary “traditional” or “learning” but rather a continuum of learning processes that are more or less supported by technology. As an example of this I really like this diagram that Phillippa Cleaves has put together,  as it shows a myriad of ways technology can intertwine with “traditional” education:

Phillippa Cleaves Technology Continuum

Phillippa Cleaves Technology Continuum

3 The choice of eLearning tools should reflect rather than determine the pedagogy of a course; how technology is used is more important than which technology is used.

This is the same for eLearning tools as with any other tool. Appropriate use of ANY tool is essential, even books, pen & paper, flip charts, whiteboards etc. from a learning design perspective I see the flow go something like: Overall learning goals > Specific learning goals > Appropriate interactions / learning processes > Appropriate tools to be used > Design of materials / activities

The selection tools used is, for the most part, the penultimate part of the learning design process.

8 – Effective eLearning practice considers the ways in which end-users will engage with the learning opportunities provided to them

This hypothesis is common sense for using any tool or resource. Having said that, practitioners should also consider and be open to unplanned ways resources may be used.

9 – The overall aim of education, that is, the development of the learner in the context of a predetermined curriculum or set of learning objectives, does not change when eLearning is applied

No, but the process of education may be expanded as learners use and master the toolset provided to support the curriculum.

Unsure about:

4 – eLearning advances primarily through the successful implementation of pedagogical innovation.

“Advances” is a very wooly term. I am sure eLearning has advanced without “successful implementation” as the pace of the industry is quicker than the capacity to research and draw results together of pedagogical success. Innovation in eLearning like all innovation is often “push” driven off the back of companies developing new technologies / services rather than “pull” from practitioners.

5 – eLearning can be used in two major ways; the presentation of education content, and the facilitation of education processes.

eLearning provides a whole range of ways its support learning, from tools to design, through to delivery. A lot of the advances in the eLearning areas are in the creation and sharing of curriculum success as OER. An example of that is Cloudworks , a collaboration between the Open University and JISC (Joint Information Systems Committee):

Cloud works banner

Cloudworks – a resource for learning practitioners to share   ideas and resources

6 – eLearning tools are best made to operate within a carefully selected and optimally integrated course design model.

I am unsure of this, simply due to the creative nature of designing and developing learning. Without experimentation and play, new ways of using technologies or even the development of doing technologies would not happen. An example of this is Twitter as a tool for learning. Originally not conceived as a carefully selected and optimally integrated tool as part of a course design model, it works well for learners and practitioners in a myriad of ways. One example being #edchat , an award winning, weekly chat about education, developed on the twitter platform. Another perspective if that of learning theories and constructivism and connectivism rely on social interaction and this in itself can create innovation around what technologies work best for the learners in their learning process. H817 itself is designed around a forum focused VLE, yet students are self organising to use Twitter as a collaboration platform.

7 – eLearning tools and techniques should be used only after consideration has been given to online vs offline trade-offs.

The perspective of this point is very much from a hypothesis driven from a classroom delivery perspective. Online learning, supported by self study,  is sometimes the only option to learners in rural or hard to reach areas. The UNESCO  and many others have a done a great deal of work in this area to consider how to support learning in areas where even classroom learning is a challenge.

10 –  Only pedagogical advantages will provide a lasting rationale for implementing eLearning approaches.

Unsure about this as many tools, techniques and technologies get taken up without a deep consideration of the advantages. A challenge here is that it is assumed that tools will work well in all settings. The way the eLearning is introduced and supported has such a critical impact. A great example are the ideas in THIS paper: “Success and Failure of e-Learning Projects: Alignment of Vision and Reality, Change and Culture”. There are clearly advantages to eLearning but there are as many, if not more barriers.

Q2  – Consider hypothesis 4 that ‘elearning advances primarily through the successful implementation of pedagogical innovation’.

As I posted above: “Advances” is a very wooly term. I am sure eLearning has advanced without “successful implementation” as the pace of the industry is quicker than the capacity to research and draw results together of pedagogical success. Innovation in eLearning like all innovation is often “push” driven off the back of companies developing new technologies / services rather than “pull” from practitioners.


I tend to link, rather than churn out here lots of references:

Nichols, M. (2003) ‘A theory for elearning’, Educational Technology & Society , vol. 6, no. 2, pp. 1–10; also available online at discussions/ discuss_march2003.html (last accessed 29 January 2016)).

Ravenscroft, A. (2001). “Designing E-learning Interactions in the 21st Century: revisiting and rethinking the role of theory.” European Journal of Education 36(2), pp.133-156

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