good hypothesis characteristics

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Characteristics Of A Good Hypothesis​

What exactly is a hypothesis.

A hypothesis is a conclusion reached after considering the evidence. This is the first step in any investigation, where the research questions are translated into a prediction. Variables, population, and the relationship between the variables are all included. A research hypothesis is a hypothesis that is tested to see if two or more variables have a relationship. Now let’s have a look at the characteristics of a  good hypothesis.

 Characteristics of

A good hypothesis has the following characteristics.

 Ability To Predict

Closest to things that can be seen, testability, relevant to the issue, techniques that are applicable, new discoveries have been made as a result of this ., harmony & consistency.

• The similarity between the two phenomena.
• Observations from previous studies, current experiences, and feedback from rivals.
• Theories based on science.
• People’s thinking processes are influenced by general patterns.
• A straightforward hypothesis
• Complex Hypothesis
• Hypothesis  with a certain direction
•  Non-direction Hypothesis
• Null Hypothesis
• Hypothesis of association and chance

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Characteristics & Qualities of a Good Hypothesis

A good hypothesis possesses the following certain attributes.

Power of Prediction

One of the valuable attribute of a good hypothesis is to predict for future. It not only clears the present problematic situation but also predict for the future that what would be happened in the coming time. So, hypothesis is a best guide of research activity due to power of prediction.

Closest to observable things

A hypothesis must have close contact with observable things. It does not believe on air castles but it is based on observation. Those things and objects which we cannot observe, for that hypothesis cannot be formulated. The verification of a hypothesis is based on observable things.

A hypothesis should be so dabble to every layman, P.V young says, “A hypothesis wo0uld be simple, if a researcher has more in sight towards the problem”. W-ocean stated that, “A hypothesis should be as sharp as razor’s blade”. So, a good hypothesis must be simple and have no complexity.

A hypothesis must be conceptually clear. It should be clear from ambiguous information’s. The terminology used in it must be clear and acceptable to everyone.

Testability

A good hypothesis should be tested empirically. It should be stated and formulated after verification and deep observation. Thus testability is the primary feature of a good hypothesis.

Relevant to Problem

If a hypothesis is relevant to a particular problem, it would be considered as good one. A hypothesis is guidance for the identification and solution of the problem, so it must be accordance to the problem.

It should be formulated for a particular and specific problem. It should not include generalization. If generalization exists, then a hypothesis cannot reach to the correct conclusions.

Relevant to available Techniques

Hypothesis must be relevant to the techniques which is available for testing. A researcher must know about the workable techniques before formulating a hypothesis.

Fruitful for new Discoveries

It should be able to provide new suggestions and ways of knowledge. It must create new discoveries of knowledge J.S. Mill, one of the eminent researcher says that “Hypothesis is the best source of new knowledge it creates new ways of discoveries”.

Consistency & Harmony

Internal harmony and consistency is a major characteristic of good hypothesis. It should be out of contradictions and conflicts. There must be a close relationship between variables which one is dependent on other.

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Good Hypothesis Statement

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Every great scientific journey begins with a well-framed hypothesis. This predictive statement serves as the backbone of a study, guiding research thesis statement with precision and purpose. Whether you’re a budding researcher or a seasoned scientist, crafting a compelling hypothesis is paramount. This guide offers a curated selection of exemplary hypothesis statements, invaluable writing insights, and best practices to ensure your research sets sail on the right course. Dive in to fortify your foundational understanding.

What is a good hypothesis statement?

A good hypothesis statement is a clear, concise, testable, and falsifiable proposition that predicts a particular outcome or relationship between variables based on prior knowledge, observation, or reasoning. It serves as the foundation for the research, guiding the direction and focus of the study.

What is an example of a strong hypothesis?

Example: “Increased exposure to sunlight (independent variable) will lead to an elevation in Vitamin D levels (dependent variable) in adults.”

This simple hypothesis is strong because it’s specific, suggesting a clear relationship between the two variables. It’s also testable, as one can measure Vitamin D levels in adults with varying exposure to sunlight, and it’s falsifiable, as findings might reveal no significant change in Vitamin D levels despite changes in sunlight exposure.

100 Good Hypothesis Statement Examples

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Crafting an impeccable thesis statement is the bedrock of any research. It’s a concise Thesis statement summary of your main point or claim. Here, we present a variety of thesis statement examples across disciplines to inspire and guide your own writing endeavors.

• Climate Change: Human activities, primarily the burning of fossil fuels and deforestation, are the main drivers behind the alarming acceleration of global warming in the past century.
• Health and Diet: Regular consumption of fast food, due to its high salt and saturated fat content, is a significant contributor to heart diseases among adults.
• Social Media: Excessive use of social media platforms has led to increased rates of anxiety and depression among teenagers.
• Economics: The 2008 financial crisis was precipitated primarily by deregulation in the financial industry and rampant speculation in the housing market.
• Literature: Shakespeare’s “Macbeth” delves into the psychological repercussions of unchecked ambition, demonstrating its corrosive impact on one’s morality.
• Education: Incorporating hands-on learning in the curriculum enhances student engagement and promotes better understanding of academic concepts.
• Technology: The proliferation of smartphones has fundamentally transformed social interactions, leading to a decline in face-to-face communication skills.
• History: The fall of the Roman Empire was a culmination of external military pressure, internal political corruption, economic decline, and social unrest.
• Art: Renaissance art glorified human form and intellect, signifying a departure from the religious-centric art of the medieval period.
• Science: Quantum mechanics challenges traditional Newtonian physics principles, introducing the concept of superposition and quantum entanglement.
• Migration: The 20th-century Great Migration of African Americans from the rural South to the urban North was driven by the quest for better economic opportunities and escape from institutionalized racism.
• Culture: The global spread of K-pop is indicative of the universal appeal of musical elements coupled with strategic marketing.
• Psychology: Childhood traumas have long-lasting implications on adult mental health, often manifesting as anxiety, depression, or PTSD.
• Gender Studies: Glass ceiling effects persist in contemporary corporate structures, hindering women from attaining top leadership positions.
• Biology: Evolutionary processes, driven by natural selection, account for the diverse species observed in the natural world.
• Philosophy: Sartre’s existentialism posits that humans are condemned to be free, bearing the weight of shaping their essence through choices.
• Law: Mandatory minimum sentencing laws have not deterred drug offenses but have exacerbated the overpopulation issue in prisons.
• Religion: The Protestant Reformation in the 16th century was a reaction against clerical abuses and the question of salvation in the Catholic Church.
• Politics: The rise of populist movements in the 21st century can be attributed to increasing economic disparities and a sense of alienation from traditional political systems.
• Environment: The decline in bee populations is intricately tied to the extensive use of pesticides, posing significant threats to global agriculture.
• Film Studies: The “Star Wars” franchise revolutionized cinematic storytelling, introducing pioneering visual effects and a uniquely immersive universe.
• Medicine: The overprescription of antibiotics has led to the emergence of superbugs resistant to conventional treatments.
• Music: The Beatles’ influence in the 60s was instrumental in shifting the paradigms of songwriting and music production.
• Anthropology: The Indus Valley Civilization’s urban planning and architecture demonstrate advanced societal structures and knowledge bases.
• Sociology: The gig economy, spurred by technological advances, has both expanded opportunities for freelancers and intensified job insecurity.
• Astronomy: The existence of exoplanets in the Goldilocks zone suggests potential for life beyond our solar system.
• Architecture: Brutalist architecture, characterized by raw concrete and geometric designs, is a reflection of the post-war era’s emphasis on functionality over aesthetics.
• Criminal Justice: Racial profiling in policing perpetuates systemic racism, undermining trust in law enforcement agencies.
• Physics: Einstein’s theory of relativity fundamentally altered our understanding of time, space, and the universe’s fabric.
• Feminism: The #MeToo movement marked a significant turning point in highlighting and combating workplace sexual harassment.
• Geography: Urbanization trends in the 21st century have led to the growth of mega-cities, with associated challenges in sustainability and infrastructure.
• Ecology: The loss of biodiversity in rainforests due to deforestation has dire implications for global climate regulation and ecosystem balance.
• Journalism: The rise of digital journalism has democratized information dissemination but has also amplified the spread of misinformation.
• Linguistics: The Sapir-Whorf hypothesis suggests that the structure of a language shapes its speakers’ worldview and cognition.
• Sports: The commercialization of sports, driven by media rights and sponsorships, has both expanded its global reach and diluted its traditional ethos.
• Theatre: Brecht’s concept of “epic theatre” sought to provoke critical thinking in audiences, promoting a detachment from emotional immersion.
• Chemistry: The discovery of the DNA double helix by Watson and Crick unveiled the molecular basis of genetics and heredity.
• Ethics: Utilitarianism, which emphasizes the greatest good for the greatest number, often conflicts with individual rights and autonomy.
• Marketing: Consumer purchasing behaviors are increasingly influenced by social media influencers, marking a shift from traditional advertising methods.
• Fashion: The fashion industry’s fast fashion model contributes significantly to environmental degradation, emphasizing the need for sustainable practices.
• Marine Biology: Coral bleaching, exacerbated by climate change, threatens the health of marine ecosystems and the livelihood of coastal communities.
• Digital Humanities: The digitization of historical archives has enhanced accessibility but raises concerns about data integrity and preservation.
• Agriculture: Genetically modified organisms (GMOs) have improved crop yields but spark debates over health implications and biodiversity.
• Military Strategy: The doctrine of Mutually Assured Destruction during the Cold War deterred direct nuclear confrontation between superpowers.
• Urban Planning: Green spaces within urban areas not only enhance aesthetics but also significantly impact residents’ mental and physical well-being.
• Public Health: Vaccination campaigns have been instrumental in eradicating diseases like smallpox, underscoring the importance of global health cooperation.
• Neuroscience: Neuroplasticity challenges the belief that the adult brain is static, highlighting its adaptability and capacity for change post-injury.
• Political Science: Globalization, while fostering economic integration, has also exacerbated nationalist sentiments and identity politics.
• Psychiatry: Cognitive-behavioral therapy has emerged as an effective treatment for a range of mental disorders, emphasizing the interplay between thought and behavior.
• Pedagogy: Incorporating multiple intelligences in teaching strategies caters to diverse learning styles, promoting holistic education.
• Robotics: The integration of artificial intelligence in robotics has opened the door to more autonomous and adaptive machines, challenging traditional job roles.
• Literature: Shakespeare’s tragic heroes, like Hamlet and Othello, exemplify the struggle between personal desires and moral responsibilities.
• Economics: The gig economy, while offering flexibility to workers, often compromises long-term job security and benefits.
• Space Exploration: The Mars colonization idea, championed by private space companies, brings forth ethical, technological, and financial challenges.
• Medieval History: The Magna Carta, signed in 1215, laid the foundational principles for constitutional monarchies and the rule of law.
• Musicology: The transition from classical to romantic era in music signified an emphasis on emotion, individualism, and the sublime.
• Anthropology: The study of Neanderthal culture challenges long-held assumptions about their cognitive capabilities and societal structures.
• Social Media: The proliferation of social media has revolutionized global communication but also poses risks related to privacy and mental health.
• Genetics: The CRISPR technology holds promise for genetic editing but raises ethical dilemmas around altering the human genome.
• Migration Studies: The Syrian refugee crisis illuminated the global community’s challenges in addressing mass migrations due to conflict.
• Climate Science: The anthropogenic factors driving global warming necessitate an immediate shift towards sustainable energy sources.
• Art History: The Renaissance marked a rebirth in art and culture, characterized by a return to classical ideals and humanism.
• Endocrinology: The role of insulin in regulating blood sugar revolutionized the understanding and treatment of diabetes.
• Cinematography: The shift from film to digital cinematography has altered filmmaking aesthetics and production processes.
• Paleontology: The discovery of feathered dinosaur fossils bridged the evolutionary gap between reptiles and birds.
• Philosophy: Existentialism, rooted in the works of Sartre and Camus, delves into human freedom, responsibility, and the search for meaning.
• Data Science: The advent of big data analytics allows businesses to personalize customer experiences but grapples with data privacy issues.
• Forensic Science: DNA fingerprinting has revolutionized criminal investigations, enabling precise identification of suspects.
• Sociology: The concept of the “melting pot” in American society has evolved into the idea of a “salad bowl,” emphasizing multicultural coexistence.
• Dermatology: The understanding of the skin’s microbiome is reshaping treatments for dermatological conditions and overall skin health.
• Archeology: The deciphering of the Rosetta Stone paved the way for understanding ancient Egyptian civilization through hieroglyphics.
• Geology: The theory of plate tectonics provided a comprehensive explanation for earthquakes, volcanic activities, and continental drift.
• Astrophysics: The detection of gravitational waves confirmed Einstein’s prediction and opened a new observational window into the cosmos.
• Nutrition: The Mediterranean diet, rich in plant-based foods and healthy fats, has been linked to longevity and reduced risk of chronic diseases.
• Mycology: The study of mycorrhizal fungi demonstrates their essential role in plant nutrient uptake and ecosystem sustainability.
• Psychology: The study of neuroplasticity reveals that the human brain remains adaptable and can recover even after traumatic injuries, challenging previous beliefs about its rigidity.
• Oceanography: The deep-sea exploration has unveiled unique bioluminescent organisms, underscoring the ocean’s vast undiscovered biodiversity.
• Architecture: The Brutalist architectural movement, marked by raw concrete structures, challenges traditional notions of aesthetics while emphasizing functionality.
• Environmental Science: The introduction of the circular economy aims to reduce waste, highlighting the need for sustainable production and consumption patterns.
• Linguistics: The extinction rate of indigenous languages has accelerated, emphasizing the urgent need for preservation initiatives.
• Neuroscience: The discovery of mirror neurons sheds light on human empathy and our ability to understand others’ emotions and intentions.
• Cultural Studies: The globalization era has witnessed a blending of cultures, leading to hybrid cultural phenomena and redefining identities.
• Astronomy: The Kepler mission’s exoplanet discoveries have rekindled the age-old debate on the possibility of life beyond Earth.
• Zoology: The study of animal migration patterns is crucial in understanding the impacts of climate change on various species.
• Political Science: The rise of populist movements worldwide challenges traditional political paradigms and reflects widespread disillusionment with the establishment.
• Urban Studies: The concept of smart cities, integrating technology into urban planning, promises more sustainable and efficient urban centers.
• Agriculture: The promotion of permaculture practices can revolutionize modern farming by enhancing soil health and biodiversity.
• Biotechnology: The development of lab-grown meat offers potential solutions to the environmental and ethical concerns associated with traditional livestock farming.
• Quantum Physics: The double-slit experiment underscores the puzzling nature of quantum mechanics, challenging our understanding of reality.
• Digital Humanities: The digitization of historical manuscripts and artifacts democratizes access to knowledge and preserves cultural heritage.
• Ecology: The reintroduction of apex predators in ecosystems, like wolves in Yellowstone, demonstrates the intricate balance of food webs.
• Sport Science: The analysis of athletes’ biomechanics offers insights into optimal performance techniques and injury prevention.
• Meteorology: The study of atmospheric aerosols is vital in understanding their role in climate change and weather patterns.
• Folklore: The evolution of folk tales across cultures underscores the universality of human emotions and shared narratives.
• Nano-technology: The synthesis of graphene has revolutionized potential applications in electronics, energy storage, and even medical devices.
• Paleontology: The discovery of feathered dinosaur fossils in China challenges traditional understanding of avian evolution, hinting at a closer relationship between birds and some dinosaur species.
• Genetics: The mapping of the human genome has opened doors for personalized medicine, emphasizing the uniqueness of each individual’s genetic code.
• Ethnomusicology: The study of indigenous tribal music reveals deep-rooted cultural expressions and the universal human connection to rhythm and melody.
• Finance: The rise of decentralized finance (DeFi) platforms challenges the traditional banking system, emphasizing the potential of blockchain in revolutionizing finance.
• Anthropology: The study of ancient human migration patterns through DNA analysis has reshaped our understanding of early human civilizations and interactions.

Good Hypothesis Statement Examples for Research

A well-structured hypothesis for research statement  sets a clear path for investigation. It should be concise, specific, and testable based on available resources.

• Sociology: Single-parent households will experience higher stress levels than two-parent households.
• Environmental Science: Urban areas with more green spaces will have lower levels of air pollution.
• Education: Use of interactive e-learning tools will improve students’ understanding of complex concepts.
• Economics: Countries with higher literacy rates will showcase better economic growth.
• Political Science: Electoral participation will increase with more youth-focused political campaigns.
• Medicine: Regular aerobic exercise will reduce the risk of cardiovascular diseases.
• Psychology: Social media usage correlates positively with feelings of loneliness in young adults.
• Linguistics: Children exposed to multilingual environments will have superior cognitive flexibility.
• Anthropology: Indigenous tribes with minimal contact with modern civilization will have unique social structures.
• Astrophysics: Star systems with exoplanets in the habitable zone are more likely to contain signs of life.

Good Hypothesis Statement Examples for Science Fair

Crafting a solid hypothesis can make a science fair project stand out. It should be based on observable phenomena and be measurable.

• Botany: Plants watered with diluted coffee will grow faster than those watered with plain water.
• Chemistry: Adding salt will increase the boiling point of water.
• Physics: The elasticity of a rubber band will decrease as it is heated.
• Biology: Yeast fermentation will produce more CO2 in sugar solutions than in plain water.
• Earth Science: Crystals will grow faster in warmer solutions than in cooler ones.
• Ecology: Pond water will contain more microbial life than tap water.
• Astronomy: Urban areas will exhibit more light pollution, affecting star visibility.
• Environmental Science: Natural cleaners are as effective as chemical-based cleaners.
• Zoology: Ants prefer sugary solutions over salty ones.
• Microbiology: Hand sanitizers with a higher percentage of alcohol will kill more bacteria.

Good Hypothesis Statement Examples for Psychology

Hypotheses in psychology delve into human behavior, emotions, and cognition, aiming to predict outcomes based on conditions or stimuli.

• Cognitive: People who multitask are more prone to distractions.
• Developmental: Early exposure to musical instruments enhances spatial reasoning.
• Social: People with higher empathy levels are better at reading facial expressions.
• Clinical: Cognitive-behavioral therapy can effectively reduce symptoms of anxiety.
• Neuropsychology: Sleep deprivation will impair short-term memory.
• Evolutionary: Altruistic behaviors have evolved because they benefit the species.
• Health: Chronic stress can lead to lower immune responses.
• Forensic: Eye-witness testimonies can be influenced by leading questions.
• Sports: Athletes perform better under moderate levels of arousal.
• Educational: Incorporating visuals in teaching will improve retention rates in students.

Good Hypothesis Statement Examples in Biology

Biology hypothesis aim to predict the relationships between living organisms and their interactions with the environment.

• Genetics: Genetically modified crops will show higher resistance to pests.
• Ecology: Forest areas with diverse flora will support a wider range of fauna.
• Physiology: Mammals in colder regions will have thicker fur.
• Cell Biology: Cells exposed to toxins will show irregular mitosis.
• Marine Biology: Coral bleaching events correlate with rising ocean temperatures.
• Evolution: Birds with longer beaks are better adapted to access deep-seated food sources.
• Botany: Plants grown in acidic soil will show stunted growth.
• Zoology: Predatory animals in isolated islands will show gigantism.
• Microbiology: Bacteria exposed to antibiotics will develop resistance over generations.
• Neurobiology: Neurons exposed to neurotoxins will show reduced firing rates.

Good Hypothesis Statement Examples in Product Management

Hypotheses in product management help in predicting user behavior and guiding product enhancements.

• UX: Incorporating a chatbot will reduce the need for customer service intervention.
• Design: A minimalist design will improve user engagement and reduce bounce rates.
• Feature Set: Introducing a dark mode will increase user retention in a mobile app.
• Functionality: A more intuitive search feature will increase product sales on an e-commerce platform.
• Accessibility: Implementing voice commands will enhance usability for visually impaired users.
• Security: Two-factor authentication will reduce the likelihood of unauthorized account access.
• Integration: Synchronizing with popular social media platforms will increase user registrations.
• Performance: Improving load times will enhance user satisfaction scores.
• Feedback: Incorporating user feedback mechanisms will lead to more relevant feature releases.
• Compatibility: Ensuring multi-device compatibility will expand the user base.

Good Hypothesis Statement Examples for Digital Marketing

n digital marketing, a hypothesis can guide strategies by predicting how certain changes might influence online behavior.

• Content: Blog posts with more visuals will have higher user engagement.
• SEO: Mobile-optimized websites will rank higher in search engine results.
• Social Media: Posts published during peak user hours will receive more engagement.
• Email Marketing: Personalized email subject lines will have a higher open rate.
• PPC: Advertisements with emotional appeal will have a higher click-through rate.
• Affiliate Marketing: Products with higher user reviews will result in more affiliate sales.
• Influencer Marketing: Collaborations with micro-influencers will yield more organic engagement.
• Video Marketing: Videos with captions will have a longer view duration.
• Retargeting: Ads targeting cart abandoners will result in higher conversion rates.
• Analytics: Implementing heatmap tools will provide clearer insights into user behavior.

Good Testable Hypothesis Statement Examples

For a t estable hypothesis , it must present a potential scenario that can be proven right or wrong through experimentation or observational studies.

• Physics: Changing the angle of a ramp will alter the speed of a rolling object.
• Botany: Increasing the amount of sunlight exposure will affect the rate of photosynthesis in plants.
• Psychology: Children who play memory-based games will perform better in short-term memory tests.
• Chemistry: The rate of reaction will increase with a rise in temperature up to a certain point.
• Astronomy: The luminosity of a star is directly related to its mass.
• Meteorology: High humidity levels will increase the perception of temperature in humans.
• Geology: The age of a rock layer is inversely proportional to its depth in undisturbed strata.
• Physiology: The amount of REM sleep is related to memory consolidation in adults.
• Microbiology: Bacteria in unsanitized water will multiply faster at room temperature than in a cold environment.
• Nutrition: Consumption of Vitamin C will reduce the duration and severity of common cold symptoms.

Good Null Hypothesis Statement Examples

A null hypothesis assumes no relationship or effect between variables and serves as a foundation to be tested against an alternative hypothesis.

• Medicine: There is no difference in recovery rates between patients taking Drug A and those taking a placebo.
• Economics: The introduction of a new fiscal policy will have no effect on employment rates.
• Biology: There is no significant difference in growth rates between plants in shaded areas and those in sunlight.
• Sociology: Attending team-building workshops has no impact on employee productivity.
• Environmental Science: The presence of a new factory has no influence on local air quality measurements.
• Linguistics: Exposure to abooks has no impact on a child’s reading capability.
• Musicology: Learning a musical instrument has no influence on mathematical ability.
• Education: Using digital textbooks versus traditional textbooks has no effect on student comprehension.
• Psychology: Meditation practices have no effect on stress levels in college students.
• Sports Science: Consuming energy drinks has no effect on short-term athletic performance.

Effective Hypothesis Statement Examples

An effective hypothesis not only offers a testable proposition but also clarifies the scope and direction of the research, making the study’s intent transparent.

• Environmental Science: The proximity to urban centers impacts the biodiversity of freshwater streams.
• Neuroscience: Exposure to blue light before bedtime affects the quality of sleep in adults.
• Anthropology: Societies with matrilineal structures have different conflict resolution strategies compared to patrilineal ones.
• Pharmacology: Patients administered Drug B will show faster recovery rates from flu symptoms than those not administered any drug.
• Zoology: Predators introduced to an isolated ecosystem will alter the behavior patterns of local prey species.
• Archeology: Civilizations with access to river routes had more expansive trade networks.
• Literary Studies: Novels from post-war periods reflect societal trauma more than novels from peaceful times.
• Physics: The density of a material will affect its rate of thermal conduction.
• Marine Biology: Coral species in deeper waters are less susceptible to bleaching events.
• Political Science: Democracies with proportional representation voting systems have more diverse legislatures.

Can a hypothesis be a question?

Hypotheses and questions both originate from scientific curiosity. However, they serve distinct roles in research. A research question and hypothesis pinpoints what the researcher is trying to discover or understand. In contrast, a hypothesis is a formulated answer to that question based on prior knowledge, observations, or educated assumptions. It’s an informed prediction that is made to be tested. For example, upon asking “Does music affect concentration?”, a researcher might hypothesize, “Listening to classical music will improve concentration levels during tasks.” It’s essential to note that the question initiates the inquiry, while the hypothesis provides direction to the research.

What are the Characteristics of Good Hypothesis?

A strong hypothesis is not merely a guess. It’s constructed with thought, precision, and a foundation in existing knowledge:

• Empirical Foundation: This means the hypothesis can be tested and proven or disproven using systematic observations or experiments.
• Definitiveness: A clear, direct statement is more actionable. Avoid general or ambiguous statements.
• Alignment with Existing Knowledge: It’s essential that your hypothesis doesn’t clash with well-established scientific theories unless there’s a valid reason to challenge them.
• Feasibility: The hypothesis should be practical and testable using available resources.

Good Hypothesis vs Bad Hypothesis Examples

Good Hypothesis: “Eating dark chocolate in moderate amounts can improve mood in adults.” Why it’s good: The hypothesis provides specificity about the type of chocolate, quantity, the target group, and the outcome.

Bad Hypothesis: “Chocolate might change feelings.” Why it’s bad: This hypothesis is overly broad, lacking specifics on the type of chocolate, the demographic, or the nature of the change in feelings.

What is the Criteria of the Good Hypothesis?

Beyond being testable, a viable hypothesis should be:

• Relevant: Directly tackles the research query.
• Objectivity: Steer clear of personal biases or beliefs. Stick to what can be tested and observed.
• Generalizability: The findings from the hypothesis should ideally apply to scenarios beyond the immediate research context, amplifying its significance.

What are the 3 things a good hypothesis should have?

For a hypothesis to be effective:

• Scope: Set boundaries. Decide what is to be studied and under what conditions.
• Directionality: Your hypothesis should indicate whether one variable will increase or decrease in the presence of another.
• Clarity in Outcome: Predict a clear outcome based on the relationship between the variables.

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

Creating a hypothesis involves more than just making an educated guess:

• Frame the Inquiry: What is your central research question? What are you hoping to uncover?
• Literature Dive: Scour existing literature on the topic. This can be academic papers, books, or trusted online sources.
• Spot the Variables: What’s changing in your experiment? What are you observing?
• Draft It: Convert your insights into a concise, testable hypothesis.
• Avoid Absolutes: Science rarely deals in certainties. Your hypothesis should reflect the possibility of being disproven.
• Iterate: As you gather more data or insights, refine your hypothesis to better fit your findings.

Tips for Writing a Good Hypothesis Statement

Crafting a hypothesis is both an art and science:

• Prioritize Simplicity: Start simple, ensuring your hypothesis is straightforward and easy to understand.
• Be Open to Change: Research is about discovery, and as you uncover more, your initial hypothesis might need tweaking.
• Avoid Assumptions: Your hypothesis should be grounded in fact, not personal beliefs.
• Seek Peer Reviews: Share your hypothesis with colleagues or mentors. They might offer valuable feedback or insights you hadn’t considered.

In essence, a hypothesis is a guiding star in the vast sky of research. It provides direction, clarity, and purpose to your investigations, ensuring your efforts are targeted and meaningful.

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How to Write a Hypothesis? Types and Examples 

All research studies involve the use of the scientific method, which is a mathematical and experimental technique used to conduct experiments by developing and testing a hypothesis or a prediction about an outcome. Simply put, a hypothesis is a suggested solution to a problem. It includes elements that are expressed in terms of relationships with each other to explain a condition or an assumption that hasn’t been verified using facts. 1 The typical steps in a scientific method include developing such a hypothesis, testing it through various methods, and then modifying it based on the outcomes of the experiments.  

A research hypothesis can be defined as a specific, testable prediction about the anticipated results of a study. 2 Hypotheses help guide the research process and supplement the aim of the study. After several rounds of testing, hypotheses can help develop scientific theories. 3 Hypotheses are often written as if-then statements. 

Here are two hypothesis examples: 

Dandelions growing in nitrogen-rich soils for two weeks develop larger leaves than those in nitrogen-poor soils because nitrogen stimulates vegetative growth. 4  

If a company offers flexible work hours, then their employees will be happier at work. 5  

Table of Contents

• What is a hypothesis? 
• Types of hypotheses 
• Characteristics of a hypothesis 
• Functions of a hypothesis 
• How to write a hypothesis 
• Hypothesis examples 
• Frequently asked questions 

What is a hypothesis?

A hypothesis expresses an expected relationship between variables in a study and is developed before conducting any research. Hypotheses are not opinions but rather are expected relationships based on facts and observations. They help support scientific research and expand existing knowledge. An incorrectly formulated hypothesis can affect the entire experiment leading to errors in the results so it’s important to know how to formulate a hypothesis and develop it carefully.

A few sources of a hypothesis include observations from prior studies, current research and experiences, competitors, scientific theories, and general conditions that can influence people. Figure 1 depicts the different steps in a research design and shows where exactly in the process a hypothesis is developed. 4  

There are seven different types of hypotheses—simple, complex, directional, nondirectional, associative and causal, null, and alternative. 

Types of hypotheses

The seven types of hypotheses are listed below: 5 , 6,7  

• Simple : Predicts the relationship between a single dependent variable and a single independent variable. 

Example: Exercising in the morning every day will increase your productivity.  

• Complex : Predicts the relationship between two or more variables. 

Example: Spending three hours or more on social media daily will negatively affect children’s mental health and productivity, more than that of adults.  

• Directional : Specifies the expected direction to be followed and uses terms like increase, decrease, positive, negative, more, or less. 

Example: The inclusion of intervention X decreases infant mortality compared to the original treatment.  

• Non-directional : Does not predict the exact direction, nature, or magnitude of the relationship between two variables but rather states the existence of a relationship. This hypothesis may be used when there is no underlying theory or if findings contradict prior research. 

Example: Cats and dogs differ in the amount of affection they express.  

• Associative and causal : An associative hypothesis suggests an interdependency between variables, that is, how a change in one variable changes the other.  

Example: There is a positive association between physical activity levels and overall health.  

A causal hypothesis, on the other hand, expresses a cause-and-effect association between variables. 

Example: Long-term alcohol use causes liver damage.  

• Null : Claims that the original hypothesis is false by showing that there is no relationship between the variables. 

Example: Sleep duration does not have any effect on productivity.  

• Alternative : States the opposite of the null hypothesis, that is, a relationship exists between two variables. 

Example: Sleep duration affects productivity.  

Characteristics of a hypothesis

So, what makes a good hypothesis? Here are some important characteristics of a hypothesis. 8,9  

• Testable : You must be able to test the hypothesis using scientific methods to either accept or reject the prediction. 
• Falsifiable : It should be possible to collect data that reject rather than support the hypothesis. 
• Logical : Hypotheses shouldn’t be a random guess but rather should be based on previous theories, observations, prior research, and logical reasoning. 
• Positive : The hypothesis statement about the existence of an association should be positive, that is, it should not suggest that an association does not exist. Therefore, the language used and knowing how to phrase a hypothesis is very important. 
• Clear and accurate : The language used should be easily comprehensible and use correct terminology. 
• Relevant : The hypothesis should be relevant and specific to the research question. 
• Structure : Should include all the elements that make a good hypothesis: variables, relationship, and outcome. 

Functions of a hypothesis

The following list mentions some important functions of a hypothesis: 1  

• Maintains the direction and progress of the research. 
• Expresses the important assumptions underlying the proposition in a single statement. 
• Establishes a suitable context for researchers to begin their investigation and for readers who are referring to the final report. 
• Provides an explanation for the occurrence of a specific phenomenon. 
• Ensures selection of appropriate and accurate facts necessary and relevant to the research subject. 

To summarize, a hypothesis provides the conceptual elements that complete the known data, conceptual relationships that systematize unordered elements, and conceptual meanings and interpretations that explain the unknown phenomena. 1  

How to write a hypothesis

Listed below are the main steps explaining how to write a hypothesis. 2,4,5  

• Make an observation and identify variables : Observe the subject in question and try to recognize a pattern or a relationship between the variables involved. This step provides essential background information to begin your research.  

For example, if you notice that an office’s vending machine frequently runs out of a specific snack, you may predict that more people in the office choose that snack over another. 

• Identify the main research question : After identifying a subject and recognizing a pattern, the next step is to ask a question that your hypothesis will answer.  

For example, after observing employees’ break times at work, you could ask “why do more employees take breaks in the morning rather than in the afternoon?” 

• Conduct some preliminary research to ensure originality and novelty : Your initial answer, which is your hypothesis, to the question is based on some pre-existing information about the subject. However, to ensure that your hypothesis has not been asked before or that it has been asked but rejected by other researchers you would need to gather additional information.  

For example, based on your observations you might state a hypothesis that employees work more efficiently when the air conditioning in the office is set at a lower temperature. However, during your preliminary research you find that this hypothesis was proven incorrect by a prior study. 

• Develop a general statement : After your preliminary research has confirmed the originality of your proposed answer, draft a general statement that includes all variables, subjects, and predicted outcome. The statement could be if/then or declarative.  
• Finalize the hypothesis statement : Use the PICOT model, which clarifies how to word a hypothesis effectively, when finalizing the statement. This model lists the important components required to write a hypothesis. 

P opulation: The specific group or individual who is the main subject of the research 

I nterest: The main concern of the study/research question 

C omparison: The main alternative group 

O utcome: The expected results  

T ime: Duration of the experiment 

Once you’ve finalized your hypothesis statement you would need to conduct experiments to test whether the hypothesis is true or false. 

Hypothesis examples

The following table provides examples of different types of hypotheses. 10 ,11  

Key takeaways  

Here’s a summary of all the key points discussed in this article about how to write a hypothesis. 

• A hypothesis is an assumption about an association between variables made based on limited evidence, which should be tested. 
• A hypothesis has four parts—the research question, independent variable, dependent variable, and the proposed relationship between the variables.   
• The statement should be clear, concise, testable, logical, and falsifiable. 
• There are seven types of hypotheses—simple, complex, directional, non-directional, associative and causal, null, and alternative. 
• A hypothesis provides a focus and direction for the research to progress. 
• A hypothesis plays an important role in the scientific method by helping to create an appropriate experimental design. 

Frequently asked questions

Hypotheses and research questions have different objectives and structure. The following table lists some major differences between the two. 9  

Here are a few examples to differentiate between a research question and hypothesis. 

Yes, here’s a simple checklist to help you gauge the effectiveness of your hypothesis. 9   1. When writing a hypothesis statement, check if it:  2. Predicts the relationship between the stated variables and the expected outcome.  3. Uses simple and concise language and is not wordy.  4. Does not assume readers’ knowledge about the subject.  5. Has observable, falsifiable, and testable results. 

As mentioned earlier in this article, a hypothesis is an assumption or prediction about an association between variables based on observations and simple evidence. These statements are usually generic. Research objectives, on the other hand, are more specific and dictated by hypotheses. The same hypothesis can be tested using different methods and the research objectives could be different in each case.     For example, Louis Pasteur observed that food lasts longer at higher altitudes, reasoned that it could be because the air at higher altitudes is cleaner (with fewer or no germs), and tested the hypothesis by exposing food to air cleaned in the laboratory. 12 Thus, a hypothesis is predictive—if the reasoning is correct, X will lead to Y—and research objectives are developed to test these predictions. 

Null hypothesis testing is a method to decide between two assumptions or predictions between variables (null and alternative hypotheses) in a statistical relationship in a sample. The null hypothesis, denoted as H 0 , claims that no relationship exists between variables in a population and any relationship in the sample reflects a sampling error or occurrence by chance. The alternative hypothesis, denoted as H 1 , claims that there is a relationship in the population. In every study, researchers need to decide whether the relationship in a sample occurred by chance or reflects a relationship in the population. This is done by hypothesis testing using the following steps: 13   1. Assume that the null hypothesis is true.  2. Determine how likely the sample relationship would be if the null hypothesis were true. This probability is called the p value.  3. If the sample relationship would be extremely unlikely, reject the null hypothesis and accept the alternative hypothesis. If the relationship would not be unlikely, accept the null hypothesis. 

To summarize, researchers should know how to write a good hypothesis to ensure that their research progresses in the required direction. A hypothesis is a testable prediction about any behavior or relationship between variables, usually based on facts and observation, and states an expected outcome.  

We hope this article has provided you with essential insight into the different types of hypotheses and their functions so that you can use them appropriately in your next research project. 

References  

• Dalen, DVV. The function of hypotheses in research. Proquest website. Accessed April 8, 2024. https://www.proquest.com/docview/1437933010?pq-origsite=gscholar&fromopenview=true&sourcetype=Scholarly%20Journals&imgSeq=1  
• McLeod S. Research hypothesis in psychology: Types & examples. SimplyPsychology website. Updated December 13, 2023. Accessed April 9, 2024. https://www.simplypsychology.org/what-is-a-hypotheses.html  
• Scientific method. Britannica website. Updated March 14, 2024. Accessed April 9, 2024. https://www.britannica.com/science/scientific-method  
• The hypothesis in science writing. Accessed April 10, 2024. https://berks.psu.edu/sites/berks/files/campus/HypothesisHandout_Final.pdf  
• How to develop a hypothesis (with elements, types, and examples). Indeed.com website. Updated February 3, 2023. Accessed April 10, 2024. https://www.indeed.com/career-advice/career-development/how-to-write-a-hypothesis  
• Types of research hypotheses. Excelsior online writing lab. Accessed April 11, 2024. https://owl.excelsior.edu/research/research-hypotheses/types-of-research-hypotheses/  
• What is a research hypothesis: how to write it, types, and examples. Researcher.life website. Published February 8, 2023. Accessed April 11, 2024. https://researcher.life/blog/article/how-to-write-a-research-hypothesis-definition-types-examples/  
• Developing a hypothesis. Pressbooks website. Accessed April 12, 2024. https://opentext.wsu.edu/carriecuttler/chapter/developing-a-hypothesis/  
• What is and how to write a good hypothesis in research. Elsevier author services website. Accessed April 12, 2024. https://scientific-publishing.webshop.elsevier.com/manuscript-preparation/what-how-write-good-hypothesis-research/  
• How to write a great hypothesis. Verywellmind website. Updated March 12, 2023. Accessed April 13, 2024. https://www.verywellmind.com/what-is-a-hypothesis-2795239  
• 15 Hypothesis examples. Helpfulprofessor.com Published September 8, 2023. Accessed March 14, 2024. https://helpfulprofessor.com/hypothesis-examples/ 
• Editage insights. What is the interconnectivity between research objectives and hypothesis? Published February 24, 2021. Accessed April 13, 2024. https://www.editage.com/insights/what-is-the-interconnectivity-between-research-objectives-and-hypothesis  
• Understanding null hypothesis testing. BCCampus open publishing. Accessed April 16, 2024. https://opentextbc.ca/researchmethods/chapter/understanding-null-hypothesis-testing/#:~:text=In%20null%20hypothesis%20testing%2C%20this,said%20to%20be%20statistically%20significant  

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2.4 Developing a Hypothesis

Learning objectives.

• Distinguish between a theory and a hypothesis.
• Discover how theories are used to generate hypotheses and how the results of studies can be used to further inform theories.
• Understand the characteristics of a good hypothesis.

Theories and Hypotheses

Before describing how to develop a hypothesis it is imporant to distinguish betwee a theory and a hypothesis. A  theory  is a coherent explanation or interpretation of one or more phenomena. Although theories can take a variety of forms, one thing they have in common is that they go beyond the phenomena they explain by including variables, structures, processes, functions, or organizing principles that have not been observed directly. Consider, for example, Zajonc’s theory of social facilitation and social inhibition. He proposed that being watched by others while performing a task creates a general state of physiological arousal, which increases the likelihood of the dominant (most likely) response. So for highly practiced tasks, being watched increases the tendency to make correct responses, but for relatively unpracticed tasks, being watched increases the tendency to make incorrect responses. Notice that this theory—which has come to be called drive theory—provides an explanation of both social facilitation and social inhibition that goes beyond the phenomena themselves by including concepts such as “arousal” and “dominant response,” along with processes such as the effect of arousal on the dominant response.

Outside of science, referring to an idea as a theory often implies that it is untested—perhaps no more than a wild guess. In science, however, the term theory has no such implication. A theory is simply an explanation or interpretation of a set of phenomena. It can be untested, but it can also be extensively tested, well supported, and accepted as an accurate description of the world by the scientific community. The theory of evolution by natural selection, for example, is a theory because it is an explanation of the diversity of life on earth—not because it is untested or unsupported by scientific research. On the contrary, the evidence for this theory is overwhelmingly positive and nearly all scientists accept its basic assumptions as accurate. Similarly, the “germ theory” of disease is a theory because it is an explanation of the origin of various diseases, not because there is any doubt that many diseases are caused by microorganisms that infect the body.

A  hypothesis , on the other hand, is a specific prediction about a new phenomenon that should be observed if a particular theory is accurate. It is an explanation that relies on just a few key concepts. Hypotheses are often specific predictions about what will happen in a particular study. They are developed by considering existing evidence and using reasoning to infer what will happen in the specific context of interest. Hypotheses are often but not always derived from theories. So a hypothesis is often a prediction based on a theory but some hypotheses are a-theoretical and only after a set of observations have been made, is a theory developed. This is because theories are broad in nature and they explain larger bodies of data. So if our research question is really original then we may need to collect some data and make some observation before we can develop a broader theory.

Theories and hypotheses always have this  if-then  relationship. “ If   drive theory is correct,  then  cockroaches should run through a straight runway faster, and a branching runway more slowly, when other cockroaches are present.” Although hypotheses are usually expressed as statements, they can always be rephrased as questions. “Do cockroaches run through a straight runway faster when other cockroaches are present?” Thus deriving hypotheses from theories is an excellent way of generating interesting research questions.

But how do researchers derive hypotheses from theories? One way is to generate a research question using the techniques discussed in this chapter  and then ask whether any theory implies an answer to that question. For example, you might wonder whether expressive writing about positive experiences improves health as much as expressive writing about traumatic experiences. Although this  question  is an interesting one  on its own, you might then ask whether the habituation theory—the idea that expressive writing causes people to habituate to negative thoughts and feelings—implies an answer. In this case, it seems clear that if the habituation theory is correct, then expressive writing about positive experiences should not be effective because it would not cause people to habituate to negative thoughts and feelings. A second way to derive hypotheses from theories is to focus on some component of the theory that has not yet been directly observed. For example, a researcher could focus on the process of habituation—perhaps hypothesizing that people should show fewer signs of emotional distress with each new writing session.

Among the very best hypotheses are those that distinguish between competing theories. For example, Norbert Schwarz and his colleagues considered two theories of how people make judgments about themselves, such as how assertive they are (Schwarz et al., 1991) [1] . Both theories held that such judgments are based on relevant examples that people bring to mind. However, one theory was that people base their judgments on the  number  of examples they bring to mind and the other was that people base their judgments on how  easily  they bring those examples to mind. To test these theories, the researchers asked people to recall either six times when they were assertive (which is easy for most people) or 12 times (which is difficult for most people). Then they asked them to judge their own assertiveness. Note that the number-of-examples theory implies that people who recalled 12 examples should judge themselves to be more assertive because they recalled more examples, but the ease-of-examples theory implies that participants who recalled six examples should judge themselves as more assertive because recalling the examples was easier. Thus the two theories made opposite predictions so that only one of the predictions could be confirmed. The surprising result was that participants who recalled fewer examples judged themselves to be more assertive—providing particularly convincing evidence in favor of the ease-of-retrieval theory over the number-of-examples theory.

Theory Testing

The primary way that scientific researchers use theories is sometimes called the hypothetico-deductive method  (although this term is much more likely to be used by philosophers of science than by scientists themselves). A researcher begins with a set of phenomena and either constructs a theory to explain or interpret them or chooses an existing theory to work with. He or she then makes a prediction about some new phenomenon that should be observed if the theory is correct. Again, this prediction is called a hypothesis. The researcher then conducts an empirical study to test the hypothesis. Finally, he or she reevaluates the theory in light of the new results and revises it if necessary. This process is usually conceptualized as a cycle because the researcher can then derive a new hypothesis from the revised theory, conduct a new empirical study to test the hypothesis, and so on. As  Figure 2.2  shows, this approach meshes nicely with the model of scientific research in psychology presented earlier in the textbook—creating a more detailed model of “theoretically motivated” or “theory-driven” research.

Figure 2.2 Hypothetico-Deductive Method Combined With the General Model of Scientific Research in Psychology Together they form a model of theoretically motivated research.

As an example, let us consider Zajonc’s research on social facilitation and inhibition. He started with a somewhat contradictory pattern of results from the research literature. He then constructed his drive theory, according to which being watched by others while performing a task causes physiological arousal, which increases an organism’s tendency to make the dominant response. This theory predicts social facilitation for well-learned tasks and social inhibition for poorly learned tasks. He now had a theory that organized previous results in a meaningful way—but he still needed to test it. He hypothesized that if his theory was correct, he should observe that the presence of others improves performance in a simple laboratory task but inhibits performance in a difficult version of the very same laboratory task. To test this hypothesis, one of the studies he conducted used cockroaches as subjects (Zajonc, Heingartner, & Herman, 1969) [2] . The cockroaches ran either down a straight runway (an easy task for a cockroach) or through a cross-shaped maze (a difficult task for a cockroach) to escape into a dark chamber when a light was shined on them. They did this either while alone or in the presence of other cockroaches in clear plastic “audience boxes.” Zajonc found that cockroaches in the straight runway reached their goal more quickly in the presence of other cockroaches, but cockroaches in the cross-shaped maze reached their goal more slowly when they were in the presence of other cockroaches. Thus he confirmed his hypothesis and provided support for his drive theory. (Zajonc also showed that drive theory existed in humans (Zajonc & Sales, 1966) [3] in many other studies afterward).

Incorporating Theory into Your Research

When you write your research report or plan your presentation, be aware that there are two basic ways that researchers usually include theory. The first is to raise a research question, answer that question by conducting a new study, and then offer one or more theories (usually more) to explain or interpret the results. This format works well for applied research questions and for research questions that existing theories do not address. The second way is to describe one or more existing theories, derive a hypothesis from one of those theories, test the hypothesis in a new study, and finally reevaluate the theory. This format works well when there is an existing theory that addresses the research question—especially if the resulting hypothesis is surprising or conflicts with a hypothesis derived from a different theory.

To use theories in your research will not only give you guidance in coming up with experiment ideas and possible projects, but it lends legitimacy to your work. Psychologists have been interested in a variety of human behaviors and have developed many theories along the way. Using established theories will help you break new ground as a researcher, not limit you from developing your own ideas.

Characteristics of a Good Hypothesis

There are three general characteristics of a good hypothesis. First, a good hypothesis must be testable and falsifiable . We must be able to test the hypothesis using the methods of science and if you’ll recall Popper’s falsifiability criterion, it must be possible to gather evidence that will disconfirm the hypothesis if it is indeed false. Second, a good hypothesis must be  logical. As described above, hypotheses are more than just a random guess. Hypotheses should be informed by previous theories or observations and logical reasoning. Typically, we begin with a broad and general theory and use  deductive reasoning to generate a more specific hypothesis to test based on that theory. Occasionally, however, when there is no theory to inform our hypothesis, we use  inductive reasoning  which involves using specific observations or research findings to form a more general hypothesis. Finally, the hypothesis should be  positive.  That is, the hypothesis should make a positive statement about the existence of a relationship or effect, rather than a statement that a relationship or effect does not exist. As scientists, we don’t set out to show that relationships do not exist or that effects do not occur so our hypotheses should not be worded in a way to suggest that an effect or relationship does not exist. The nature of science is to assume that something does not exist and then seek to find evidence to prove this wrong, to show that really it does exist. That may seem backward to you but that is the nature of the scientific method. The underlying reason for this is beyond the scope of this chapter but it has to do with statistical theory.

Key Takeaways

• A theory is broad in nature and explains larger bodies of data. A hypothesis is more specific and makes a prediction about the outcome of a particular study.
• Working with theories is not “icing on the cake.” It is a basic ingredient of psychological research.
• Like other scientists, psychologists use the hypothetico-deductive method. They construct theories to explain or interpret phenomena (or work with existing theories), derive hypotheses from their theories, test the hypotheses, and then reevaluate the theories in light of the new results.
• Practice: Find a recent empirical research report in a professional journal. Read the introduction and highlight in different colors descriptions of theories and hypotheses.
• Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simons, A. (1991). Ease of retrieval as information: Another look at the availability heuristic.  Journal of Personality and Social Psychology, 61 , 195–202. ↵
• Zajonc, R. B., Heingartner, A., & Herman, E. M. (1969). Social enhancement and impairment of performance in the cockroach.  Journal of Personality and Social Psychology, 13 , 83–92. ↵
• Zajonc, R.B. & Sales, S.M. (1966). Social facilitation of dominant and subordinate responses. Journal of Experimental Social Psychology, 2 , 160-168. ↵

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What is a Research Hypothesis: How to Write it, Types, and Examples

Any research begins with a research question and a research hypothesis . A research question alone may not suffice to design the experiment(s) needed to answer it. A hypothesis is central to the scientific method. But what is a hypothesis ? A hypothesis is a testable statement that proposes a possible explanation to a phenomenon, and it may include a prediction. Next, you may ask what is a research hypothesis ? Simply put, a research hypothesis is a prediction or educated guess about the relationship between the variables that you want to investigate.  

It is important to be thorough when developing your research hypothesis. Shortcomings in the framing of a hypothesis can affect the study design and the results. A better understanding of the research hypothesis definition and characteristics of a good hypothesis will make it easier for you to develop your own hypothesis for your research. Let’s dive in to know more about the types of research hypothesis , how to write a research hypothesis , and some research hypothesis examples .  

Table of Contents

What is a hypothesis ?  

A hypothesis is based on the existing body of knowledge in a study area. Framed before the data are collected, a hypothesis states the tentative relationship between independent and dependent variables, along with a prediction of the outcome.  

What is a research hypothesis ?  

Young researchers starting out their journey are usually brimming with questions like “ What is a hypothesis ?” “ What is a research hypothesis ?” “How can I write a good research hypothesis ?”   

A research hypothesis is a statement that proposes a possible explanation for an observable phenomenon or pattern. It guides the direction of a study and predicts the outcome of the investigation. A research hypothesis is testable, i.e., it can be supported or disproven through experimentation or observation.     

Characteristics of a good hypothesis  

Here are the characteristics of a good hypothesis :  

• Clearly formulated and free of language errors and ambiguity  
• Concise and not unnecessarily verbose  
• Has clearly defined variables  
• Testable and stated in a way that allows for it to be disproven  
• Can be tested using a research design that is feasible, ethical, and practical   
• Specific and relevant to the research problem  
• Rooted in a thorough literature search  
• Can generate new knowledge or understanding

How to create an effective research hypothesis  

A study begins with the formulation of a research question. A researcher then performs background research. This background information forms the basis for building a good research hypothesis . The researcher then performs experiments, collects, and analyzes the data, interprets the findings, and ultimately, determines if the findings support or negate the original hypothesis.  

Let’s look at each step for creating an effective, testable, and good research hypothesis :  

• Identify a research problem or question: Start by identifying a specific research problem.   
• Review the literature: Conduct an in-depth review of the existing literature related to the research problem to grasp the current knowledge and gaps in the field.   
• Formulate a clear and testable hypothesis : Based on the research question, use existing knowledge to form a clear and testable hypothesis . The hypothesis should state a predicted relationship between two or more variables that can be measured and manipulated. Improve the original draft till it is clear and meaningful.  
• State the null hypothesis: The null hypothesis is a statement that there is no relationship between the variables you are studying.   
• Define the population and sample: Clearly define the population you are studying and the sample you will be using for your research.  
• Select appropriate methods for testing the hypothesis: Select appropriate research methods, such as experiments, surveys, or observational studies, which will allow you to test your research hypothesis .  

Remember that creating a research hypothesis is an iterative process, i.e., you might have to revise it based on the data you collect. You may need to test and reject several hypotheses before answering the research problem.  

How to write a research hypothesis  

When you start writing a research hypothesis , you use an “if–then” statement format, which states the predicted relationship between two or more variables. Clearly identify the independent variables (the variables being changed) and the dependent variables (the variables being measured), as well as the population you are studying. Review and revise your hypothesis as needed.  

An example of a research hypothesis in this format is as follows:  

“ If [athletes] follow [cold water showers daily], then their [endurance] increases.”  

Population: athletes  

Independent variable: daily cold water showers  

Dependent variable: endurance  

You may have understood the characteristics of a good hypothesis . But note that a research hypothesis is not always confirmed; a researcher should be prepared to accept or reject the hypothesis based on the study findings.  

Research hypothesis checklist  

Following from above, here is a 10-point checklist for a good research hypothesis :  

• Testable: A research hypothesis should be able to be tested via experimentation or observation.  
• Specific: A research hypothesis should clearly state the relationship between the variables being studied.  
• Based on prior research: A research hypothesis should be based on existing knowledge and previous research in the field.  
• Falsifiable: A research hypothesis should be able to be disproven through testing.  
• Clear and concise: A research hypothesis should be stated in a clear and concise manner.  
• Logical: A research hypothesis should be logical and consistent with current understanding of the subject.  
• Relevant: A research hypothesis should be relevant to the research question and objectives.  
• Feasible: A research hypothesis should be feasible to test within the scope of the study.  
• Reflects the population: A research hypothesis should consider the population or sample being studied.  
• Uncomplicated: A good research hypothesis is written in a way that is easy for the target audience to understand.  

By following this research hypothesis checklist , you will be able to create a research hypothesis that is strong, well-constructed, and more likely to yield meaningful results.  

Types of research hypothesis  

Different types of research hypothesis are used in scientific research:  

1. Null hypothesis:

A null hypothesis states that there is no change in the dependent variable due to changes to the independent variable. This means that the results are due to chance and are not significant. A null hypothesis is denoted as H0 and is stated as the opposite of what the alternative hypothesis states.   

Example: “ The newly identified virus is not zoonotic .”  

2. Alternative hypothesis:

This states that there is a significant difference or relationship between the variables being studied. It is denoted as H1 or Ha and is usually accepted or rejected in favor of the null hypothesis.  

Example: “ The newly identified virus is zoonotic .”  

3. Directional hypothesis :

This specifies the direction of the relationship or difference between variables; therefore, it tends to use terms like increase, decrease, positive, negative, more, or less.   

Example: “ The inclusion of intervention X decreases infant mortality compared to the original treatment .”   

4. Non-directional hypothesis:

While it does not predict the exact direction or nature of the relationship between the two variables, a non-directional hypothesis states the existence of a relationship or difference between variables but not the direction, nature, or magnitude of the relationship. A non-directional hypothesis may be used when there is no underlying theory or when findings contradict previous research.  

Example, “ Cats and dogs differ in the amount of affection they express .”  

5. Simple hypothesis :

A simple hypothesis only predicts the relationship between one independent and another independent variable.  

Example: “ Applying sunscreen every day slows skin aging .”  

6 . Complex hypothesis :

A complex hypothesis states the relationship or difference between two or more independent and dependent variables.   

Example: “ Applying sunscreen every day slows skin aging, reduces sun burn, and reduces the chances of skin cancer .” (Here, the three dependent variables are slowing skin aging, reducing sun burn, and reducing the chances of skin cancer.)  

7. Associative hypothesis:  

An associative hypothesis states that a change in one variable results in the change of the other variable. The associative hypothesis defines interdependency between variables.  

Example: “ There is a positive association between physical activity levels and overall health .”  

8 . Causal hypothesis:

A causal hypothesis proposes a cause-and-effect interaction between variables.  

Example: “ Long-term alcohol use causes liver damage .”  

Note that some of the types of research hypothesis mentioned above might overlap. The types of hypothesis chosen will depend on the research question and the objective of the study.  

Research hypothesis examples  

Here are some good research hypothesis examples :  

“The use of a specific type of therapy will lead to a reduction in symptoms of depression in individuals with a history of major depressive disorder.”  

“Providing educational interventions on healthy eating habits will result in weight loss in overweight individuals.”  

“Plants that are exposed to certain types of music will grow taller than those that are not exposed to music.”  

“The use of the plant growth regulator X will lead to an increase in the number of flowers produced by plants.”  

Characteristics that make a research hypothesis weak are unclear variables, unoriginality, being too general or too vague, and being untestable. A weak hypothesis leads to weak research and improper methods.   

Some bad research hypothesis examples (and the reasons why they are “bad”) are as follows:  

“This study will show that treatment X is better than any other treatment . ” (This statement is not testable, too broad, and does not consider other treatments that may be effective.)  

“This study will prove that this type of therapy is effective for all mental disorders . ” (This statement is too broad and not testable as mental disorders are complex and different disorders may respond differently to different types of therapy.)  

“Plants can communicate with each other through telepathy . ” (This statement is not testable and lacks a scientific basis.)  

Importance of testable hypothesis  

If a research hypothesis is not testable, the results will not prove or disprove anything meaningful. The conclusions will be vague at best. A testable hypothesis helps a researcher focus on the study outcome and understand the implication of the question and the different variables involved. A testable hypothesis helps a researcher make precise predictions based on prior research.  

To be considered testable, there must be a way to prove that the hypothesis is true or false; further, the results of the hypothesis must be reproducible.  

Frequently Asked Questions (FAQs) on research hypothesis  

1. What is the difference between research question and research hypothesis ?  

A research question defines the problem and helps outline the study objective(s). It is an open-ended statement that is exploratory or probing in nature. Therefore, it does not make predictions or assumptions. It helps a researcher identify what information to collect. A research hypothesis , however, is a specific, testable prediction about the relationship between variables. Accordingly, it guides the study design and data analysis approach.

2. When to reject null hypothesis ?

A null hypothesis should be rejected when the evidence from a statistical test shows that it is unlikely to be true. This happens when the test statistic (e.g., p -value) is less than the defined significance level (e.g., 0.05). Rejecting the null hypothesis does not necessarily mean that the alternative hypothesis is true; it simply means that the evidence found is not compatible with the null hypothesis.  

3. How can I be sure my hypothesis is testable?  

A testable hypothesis should be specific and measurable, and it should state a clear relationship between variables that can be tested with data. To ensure that your hypothesis is testable, consider the following:  

• Clearly define the key variables in your hypothesis. You should be able to measure and manipulate these variables in a way that allows you to test the hypothesis.  
• The hypothesis should predict a specific outcome or relationship between variables that can be measured or quantified.   
• You should be able to collect the necessary data within the constraints of your study.  
• It should be possible for other researchers to replicate your study, using the same methods and variables.   
• Your hypothesis should be testable by using appropriate statistical analysis techniques, so you can draw conclusions, and make inferences about the population from the sample data.  
• The hypothesis should be able to be disproven or rejected through the collection of data.  

4. How do I revise my research hypothesis if my data does not support it?  

If your data does not support your research hypothesis , you will need to revise it or develop a new one. You should examine your data carefully and identify any patterns or anomalies, re-examine your research question, and/or revisit your theory to look for any alternative explanations for your results. Based on your review of the data, literature, and theories, modify your research hypothesis to better align it with the results you obtained. Use your revised hypothesis to guide your research design and data collection. It is important to remain objective throughout the process.  

5. I am performing exploratory research. Do I need to formulate a research hypothesis?  

As opposed to “confirmatory” research, where a researcher has some idea about the relationship between the variables under investigation, exploratory research (or hypothesis-generating research) looks into a completely new topic about which limited information is available. Therefore, the researcher will not have any prior hypotheses. In such cases, a researcher will need to develop a post-hoc hypothesis. A post-hoc research hypothesis is generated after these results are known.  

6. How is a research hypothesis different from a research question?

A research question is an inquiry about a specific topic or phenomenon, typically expressed as a question. It seeks to explore and understand a particular aspect of the research subject. In contrast, a research hypothesis is a specific statement or prediction that suggests an expected relationship between variables. It is formulated based on existing knowledge or theories and guides the research design and data analysis.

7. Can a research hypothesis change during the research process?

Yes, research hypotheses can change during the research process. As researchers collect and analyze data, new insights and information may emerge that require modification or refinement of the initial hypotheses. This can be due to unexpected findings, limitations in the original hypotheses, or the need to explore additional dimensions of the research topic. Flexibility is crucial in research, allowing for adaptation and adjustment of hypotheses to align with the evolving understanding of the subject matter.

8. How many hypotheses should be included in a research study?

The number of research hypotheses in a research study varies depending on the nature and scope of the research. It is not necessary to have multiple hypotheses in every study. Some studies may have only one primary hypothesis, while others may have several related hypotheses. The number of hypotheses should be determined based on the research objectives, research questions, and the complexity of the research topic. It is important to ensure that the hypotheses are focused, testable, and directly related to the research aims.

9. Can research hypotheses be used in qualitative research?

Yes, research hypotheses can be used in qualitative research, although they are more commonly associated with quantitative research. In qualitative research, hypotheses may be formulated as tentative or exploratory statements that guide the investigation. Instead of testing hypotheses through statistical analysis, qualitative researchers may use the hypotheses to guide data collection and analysis, seeking to uncover patterns, themes, or relationships within the qualitative data. The emphasis in qualitative research is often on generating insights and understanding rather than confirming or rejecting specific research hypotheses through statistical testing.

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What Are the Elements of a Good Hypothesis?

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A hypothesis is an educated guess or prediction of what will happen. In science, a hypothesis proposes a relationship between factors called variables. A good hypothesis relates an independent variable and a dependent variable. The effect on the dependent variable depends on or is determined by what happens when you change the independent variable . While you could consider any prediction of an outcome to be a type of hypothesis, a good hypothesis is one you can test using the scientific method. In other words, you want to propose a hypothesis to use as the basis for an experiment.

Cause and Effect or 'If, Then' Relationships

A good experimental hypothesis can be written as an if, then statement to establish cause and effect on the variables. If you make a change to the independent variable, then the dependent variable will respond. Here's an example of a hypothesis:

If you increase the duration of light, (then) corn plants will grow more each day.

The hypothesis establishes two variables, length of light exposure, and the rate of plant growth. An experiment could be designed to test whether the rate of growth depends on the duration of light. The duration of light is the independent variable, which you can control in an experiment . The rate of plant growth is the dependent variable, which you can measure and record as data in an experiment.

Key Points of Hypothesis

When you have an idea for a hypothesis, it may help to write it out in several different ways. Review your choices and select a hypothesis that accurately describes what you are testing.

• Does the hypothesis relate an independent and dependent variable? Can you identify the variables?
• Can you test the hypothesis? In other words, could you design an experiment that would allow you to establish or disprove a relationship between the variables?
• Would your experiment be safe and ethical?
• Is there a simpler or more precise way to state the hypothesis? If so, rewrite it.

What If the Hypothesis Is Incorrect?

It's not wrong or bad if the hypothesis is not supported or is incorrect. Actually, this outcome may tell you more about a relationship between the variables than if the hypothesis is supported. You may intentionally write your hypothesis as a null hypothesis or no-difference hypothesis to establish a relationship between the variables.

For example, the hypothesis:

The rate of corn plant growth does not depend on the duration of light.

This can be tested by exposing corn plants to different length "days" and measuring the rate of plant growth. A statistical test can be applied to measure how well the data support the hypothesis. If the hypothesis is not supported, then you have evidence of a relationship between the variables. It's easier to establish cause and effect by testing whether "no effect" is found. Alternatively, if the null hypothesis is supported, then you have shown the variables are not related. Either way, your experiment is a success.

Need more examples of how to write a hypothesis ? Here you go:

• If you turn out all the lights, you will fall asleep faster. (Think: How would you test it?)
• If you drop different objects, they will fall at the same rate.
• If you eat only fast food, then you will gain weight.
• If you use cruise control, then your car will get better gas mileage.
• If you apply a top coat, then your manicure will last longer.
• If you turn the lights on and off rapidly, then the bulb will burn out faster.
• What Is a Testable Hypothesis?
• What Are Examples of a Hypothesis?
• What Is a Hypothesis? (Science)
• Scientific Hypothesis Examples
• Six Steps of the Scientific Method
• Scientific Method Flow Chart
• Null Hypothesis Examples
• Understanding Simple vs Controlled Experiments
• Scientific Method Vocabulary Terms
• What Is a Controlled Experiment?
• Scientific Variable
• What Is an Experimental Constant?
• What Is the Difference Between a Control Variable and Control Group?
• DRY MIX Experiment Variables Acronym
• Random Error vs. Systematic Error
• The Role of a Controlled Variable in an Experiment

Research Hypothesis – Types, Examples Characteristics, and Sources

Research hypothesis.

A research hypothesis is referred to as a scientific hypothesis. This is a clear, specific, and testable statement that predicts the expected result in a scientific study. It is a prediction, reasonable guess, and logical supposition about the relationship between the variables. A research hypothesis is an integral and central part of research whether it is exploratory or explanatory, qualitative or quantitative. It creates the base of scientific experiments. So, you must be very careful while building any hypothesis.

A hypothesis can be correct or wrong. It is tested through experiments or research to determine whether it is correct or incorrect.

Functions of research  hypothesis

There are major functions of research hypothesis that are as follow:

• It helps in making observations and experiments possible.
• It is the basic point for the research.
• It verifies the observations.
• It leads the inquiries in the right regulation.
• It provides the extension of knowledge.
• It helps to explore different aspects of the research.
• It introduces different research techniques.
• It ensures the precision and accuracy of the results of the research.
• It enables the researcher to be focused. Because without a hypothesis, he may focus on unnecessary aspects and wastes his resources like time, money, and effort.

Sources of hypothesis

Following are the sources of the hypothesis:

• Scientific theories
• Personal experience
• Observation
• Imagination and thinking
• Previous study
• General patterns

Characteristics of an effective research hypothesis

Following are the characteristics of an effective research hypothesis:

• It must be logical.
• It must be simple and clear.
• It needs to be precise.
• It must identify the research objectives.
• It must be empirically testable with experimentation and research.
• It must be manageable.
• It must be relevant and specific to the theme of the research.
• It must be predictable.
• It must be falsifiable.
• It must be neither specific nor general.
• It must be considered valuable even if it proves false.

Types of research hypothesis

Following are the types of research hypotheses.

• Simple hypothesis

It shows a relationship between a single dependent variable and an independent variable. For instance, if you take in more carbs and fats, you will gain obesity. Here taking more carbs and fats are an independent variable and gaining weight is the dependent variable.

• Complex hypothesis

It predicts the relationship between two or more independent variables and dependent variables. For example, we can say that taking in more carbs and fats can cause obesity along with other problems like high blood pressure, heart disease, and so on.

• Directional hypothesis 

Typically, directional hypotheses are derived from theory. This type of hypothesis shows the researcher’s intellectual commitment towards a specific outcome. The researcher predicts the existence and nature of a relationship between variables.

• Non-directional hypothesis

The non-directional hypothesis is used when there is no theory and the findings of studies are contradictory.  It shows the relationship between two variables but does not set down the expected direction or nature of the relationship.

• Null hypothesis

Null hypotheses are made when there is no empirical and adequate theoretical information to show a hypothesis. The null hypothesis negates the relationship between variables. It is denoted by Ho. This hypothesis is made when the researcher wants to reject or disapprove the null hypothesis. It is contrary to what an experimenter or investigator expects. The purpose is to confirm the existence of a relationship between the variables.

The null hypothesis can be:

• Associative or causal
• Simple or complex

1. Alternative hypothesis

When a hypothesis is rejected, then another hypothesis is made to be tested and show the desired results. This is called an alternative hypothesis. It is opposite to the null hypothesis and is made to disprove that hypothesis. This hypothesis is denoted by H1.

2. Statistical hypothesis

As the name mentions, this hypothesis has the quality to be verified statistically. It is tested by using quantitative techniques. The variables in this hypothesis are quantifiable and can also transform into quantifiable indicators to verify it statistically.

• Empirical hypothesis

This hypothesis is used when a theory is tested with observation and experiment. It is just a notion or idea. This hypothesis goes through trial and error by changing independent variables. The series of trial and error helps to find the best result. The outcomes of these experiments can be proven over time.

• Associative and causal hypothesis

The associative hypothesis shows interdependency between variables. Any change in one variable causes the change in another variable. Whereas, the causal hypothesis shows a cause and effect between variables.

How to formulate a research hypothesis

There are some important points you must consider while formulating a hypothesis:

• Ask a question

The first and foremost thing for creating a research hypothesis is to generate a research question. The question should be specific, focused, and researchable within the limitations of your project.

• Do preliminary research

Now try to find the answer to your question. The initial answer must be based on previous knowledge about the topic. Concern theories and previous studies and try to form assumptions about what you will find in your research.

Create a conceptual framework about different variables you are going to study and the relationships between them.

• Formulate the hypothesis

Now you have an idea of what you are expecting to find. Make a clear and concise answer to the question.

• Refine your hypothesis

Now check whether your hypothesis is testable. There must be clear definitions of your hypothesis while phrasing. It should contain:

• The relevant variables

The particular group being studied.

The predicted result of the analysis or experiment

• Phrase your hypothesis in three ways

To recognize the variables, write a prediction in (if-then) form. Like, if a particular action is taken, a certain result is expected. The first part of the phrase shows the independent variable while the second part shows the dependent variable.

• Write a null hypothesis

If the research requires statistical hypothesis testing, you must have to make a null hypothesis and an alternative hypothesis.

Now test your hypothesis through observations, techniques, and experiments by keeping necessary things and resources in consideration.

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Overview of the Scientific Method

Learning Objectives

• Distinguish between a theory and a hypothesis.
• Discover how theories are used to generate hypotheses and how the results of studies can be used to further inform theories.
• Understand the characteristics of a good hypothesis.

Theories and Hypotheses

Before describing how to develop a hypothesis, it is important to distinguish between a theory and a hypothesis. A  theory  is a coherent explanation or interpretation of one or more phenomena. Although theories can take a variety of forms, one thing they have in common is that they go beyond the phenomena they explain by including variables, structures, processes, functions, or organizing principles that have not been observed directly. Consider, for example, Zajonc’s theory of social facilitation and social inhibition (1965) [1] . He proposed that being watched by others while performing a task creates a general state of physiological arousal, which increases the likelihood of the dominant (most likely) response. So for highly practiced tasks, being watched increases the tendency to make correct responses, but for relatively unpracticed tasks, being watched increases the tendency to make incorrect responses. Notice that this theory—which has come to be called drive theory—provides an explanation of both social facilitation and social inhibition that goes beyond the phenomena themselves by including concepts such as “arousal” and “dominant response,” along with processes such as the effect of arousal on the dominant response.

Outside of science, referring to an idea as a theory often implies that it is untested—perhaps no more than a wild guess. In science, however, the term theory has no such implication. A theory is simply an explanation or interpretation of a set of phenomena. It can be untested, but it can also be extensively tested, well supported, and accepted as an accurate description of the world by the scientific community. The theory of evolution by natural selection, for example, is a theory because it is an explanation of the diversity of life on earth—not because it is untested or unsupported by scientific research. On the contrary, the evidence for this theory is overwhelmingly positive and nearly all scientists accept its basic assumptions as accurate. Similarly, the “germ theory” of disease is a theory because it is an explanation of the origin of various diseases, not because there is any doubt that many diseases are caused by microorganisms that infect the body.

A  hypothesis , on the other hand, is a specific prediction about a new phenomenon that should be observed if a particular theory is accurate. It is an explanation that relies on just a few key concepts. Hypotheses are often specific predictions about what will happen in a particular study. They are developed by considering existing evidence and using reasoning to infer what will happen in the specific context of interest. Hypotheses are often but not always derived from theories. So a hypothesis is often a prediction based on a theory but some hypotheses are a-theoretical and only after a set of observations have been made, is a theory developed. This is because theories are broad in nature and they explain larger bodies of data. So if our research question is really original then we may need to collect some data and make some observations before we can develop a broader theory.

Theories and hypotheses always have this  if-then  relationship. “ If   drive theory is correct,  then  cockroaches should run through a straight runway faster, and a branching runway more slowly, when other cockroaches are present.” Although hypotheses are usually expressed as statements, they can always be rephrased as questions. “Do cockroaches run through a straight runway faster when other cockroaches are present?” Thus deriving hypotheses from theories is an excellent way of generating interesting research questions.

But how do researchers derive hypotheses from theories? One way is to generate a research question using the techniques discussed in this chapter  and then ask whether any theory implies an answer to that question. For example, you might wonder whether expressive writing about positive experiences improves health as much as expressive writing about traumatic experiences. Although this  question  is an interesting one  on its own, you might then ask whether the habituation theory—the idea that expressive writing causes people to habituate to negative thoughts and feelings—implies an answer. In this case, it seems clear that if the habituation theory is correct, then expressive writing about positive experiences should not be effective because it would not cause people to habituate to negative thoughts and feelings. A second way to derive hypotheses from theories is to focus on some component of the theory that has not yet been directly observed. For example, a researcher could focus on the process of habituation—perhaps hypothesizing that people should show fewer signs of emotional distress with each new writing session.

Among the very best hypotheses are those that distinguish between competing theories. For example, Norbert Schwarz and his colleagues considered two theories of how people make judgments about themselves, such as how assertive they are (Schwarz et al., 1991) [2] . Both theories held that such judgments are based on relevant examples that people bring to mind. However, one theory was that people base their judgments on the  number  of examples they bring to mind and the other was that people base their judgments on how  easily  they bring those examples to mind. To test these theories, the researchers asked people to recall either six times when they were assertive (which is easy for most people) or 12 times (which is difficult for most people). Then they asked them to judge their own assertiveness. Note that the number-of-examples theory implies that people who recalled 12 examples should judge themselves to be more assertive because they recalled more examples, but the ease-of-examples theory implies that participants who recalled six examples should judge themselves as more assertive because recalling the examples was easier. Thus the two theories made opposite predictions so that only one of the predictions could be confirmed. The surprising result was that participants who recalled fewer examples judged themselves to be more assertive—providing particularly convincing evidence in favor of the ease-of-retrieval theory over the number-of-examples theory.

Theory Testing

The primary way that scientific researchers use theories is sometimes called the hypothetico-deductive method  (although this term is much more likely to be used by philosophers of science than by scientists themselves). Researchers begin with a set of phenomena and either construct a theory to explain or interpret them or choose an existing theory to work with. They then make a prediction about some new phenomenon that should be observed if the theory is correct. Again, this prediction is called a hypothesis. The researchers then conduct an empirical study to test the hypothesis. Finally, they reevaluate the theory in light of the new results and revise it if necessary. This process is usually conceptualized as a cycle because the researchers can then derive a new hypothesis from the revised theory, conduct a new empirical study to test the hypothesis, and so on. As  Figure 2.3  shows, this approach meshes nicely with the model of scientific research in psychology presented earlier in the textbook—creating a more detailed model of “theoretically motivated” or “theory-driven” research.

As an example, let us consider Zajonc’s research on social facilitation and inhibition. He started with a somewhat contradictory pattern of results from the research literature. He then constructed his drive theory, according to which being watched by others while performing a task causes physiological arousal, which increases an organism’s tendency to make the dominant response. This theory predicts social facilitation for well-learned tasks and social inhibition for poorly learned tasks. He now had a theory that organized previous results in a meaningful way—but he still needed to test it. He hypothesized that if his theory was correct, he should observe that the presence of others improves performance in a simple laboratory task but inhibits performance in a difficult version of the very same laboratory task. To test this hypothesis, one of the studies he conducted used cockroaches as subjects (Zajonc, Heingartner, & Herman, 1969) [3] . The cockroaches ran either down a straight runway (an easy task for a cockroach) or through a cross-shaped maze (a difficult task for a cockroach) to escape into a dark chamber when a light was shined on them. They did this either while alone or in the presence of other cockroaches in clear plastic “audience boxes.” Zajonc found that cockroaches in the straight runway reached their goal more quickly in the presence of other cockroaches, but cockroaches in the cross-shaped maze reached their goal more slowly when they were in the presence of other cockroaches. Thus he confirmed his hypothesis and provided support for his drive theory. (Zajonc also showed that drive theory existed in humans [Zajonc & Sales, 1966] [4] in many other studies afterward).

Incorporating Theory into Your Research

When you write your research report or plan your presentation, be aware that there are two basic ways that researchers usually include theory. The first is to raise a research question, answer that question by conducting a new study, and then offer one or more theories (usually more) to explain or interpret the results. This format works well for applied research questions and for research questions that existing theories do not address. The second way is to describe one or more existing theories, derive a hypothesis from one of those theories, test the hypothesis in a new study, and finally reevaluate the theory. This format works well when there is an existing theory that addresses the research question—especially if the resulting hypothesis is surprising or conflicts with a hypothesis derived from a different theory.

To use theories in your research will not only give you guidance in coming up with experiment ideas and possible projects, but it lends legitimacy to your work. Psychologists have been interested in a variety of human behaviors and have developed many theories along the way. Using established theories will help you break new ground as a researcher, not limit you from developing your own ideas.

Characteristics of a Good Hypothesis

There are three general characteristics of a good hypothesis. First, a good hypothesis must be testable and falsifiable . We must be able to test the hypothesis using the methods of science and if you’ll recall Popper’s falsifiability criterion, it must be possible to gather evidence that will disconfirm the hypothesis if it is indeed false. Second, a good hypothesis must be logical. As described above, hypotheses are more than just a random guess. Hypotheses should be informed by previous theories or observations and logical reasoning. Typically, we begin with a broad and general theory and use  deductive reasoning to generate a more specific hypothesis to test based on that theory. Occasionally, however, when there is no theory to inform our hypothesis, we use  inductive reasoning  which involves using specific observations or research findings to form a more general hypothesis. Finally, the hypothesis should be positive. That is, the hypothesis should make a positive statement about the existence of a relationship or effect, rather than a statement that a relationship or effect does not exist. As scientists, we don’t set out to show that relationships do not exist or that effects do not occur so our hypotheses should not be worded in a way to suggest that an effect or relationship does not exist. The nature of science is to assume that something does not exist and then seek to find evidence to prove this wrong, to show that it really does exist. That may seem backward to you but that is the nature of the scientific method. The underlying reason for this is beyond the scope of this chapter but it has to do with statistical theory.

• Zajonc, R. B. (1965). Social facilitation.  Science, 149 , 269–274 ↵
• Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simons, A. (1991). Ease of retrieval as information: Another look at the availability heuristic.  Journal of Personality and Social Psychology, 61 , 195–202. ↵
• Zajonc, R. B., Heingartner, A., & Herman, E. M. (1969). Social enhancement and impairment of performance in the cockroach.  Journal of Personality and Social Psychology, 13 , 83–92. ↵
• Zajonc, R.B. & Sales, S.M. (1966). Social facilitation of dominant and subordinate responses. Journal of Experimental Social Psychology, 2 , 160-168. ↵

A coherent explanation or interpretation of one or more phenomena.

A specific prediction about a new phenomenon that should be observed if a particular theory is accurate.

A cyclical process of theory development, starting with an observed phenomenon, then developing or using a theory to make a specific prediction of what should happen if that theory is correct, testing that prediction, refining the theory in light of the findings, and using that refined theory to develop new hypotheses, and so on.

The ability to test the hypothesis using the methods of science and the possibility to gather evidence that will disconfirm the hypothesis if it is indeed false.

Research Methods in Psychology Copyright © 2019 by Rajiv S. Jhangiani, I-Chant A. Chiang, Carrie Cuttler, & Dana C. Leighton is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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