hypothesis of biology

Hypothesis n., plural: hypotheses [/haɪˈpɑːθəsɪs/] Definition: Testable scientific prediction

Table of Contents

What Is Hypothesis?

A scientific hypothesis is a foundational element of the scientific method . It’s a testable statement proposing a potential explanation for natural phenomena. The term hypothesis means “little theory” . A hypothesis is a short statement that can be tested and gives a possible reason for a phenomenon or a possible link between two variables . In the setting of scientific research, a hypothesis is a tentative explanation or statement that can be proven wrong and is used to guide experiments and empirical research.

It is an important part of the scientific method because it gives a basis for planning tests, gathering data, and judging evidence to see if it is true and could help us understand how natural things work. Several hypotheses can be tested in the real world, and the results of careful and systematic observation and analysis can be used to support, reject, or improve them.

Researchers and scientists often use the word hypothesis to refer to this educated guess . These hypotheses are firmly established based on scientific principles and the rigorous testing of new technology and experiments .

For example, in astrophysics, the Big Bang Theory is a working hypothesis that explains the origins of the universe and considers it as a natural phenomenon. It is among the most prominent scientific hypotheses in the field.

“The scientific method: steps, terms, and examples” by Scishow:

Biology definition: A hypothesis  is a supposition or tentative explanation for (a group of) phenomena, (a set of) facts, or a scientific inquiry that may be tested, verified or answered by further investigation or methodological experiment. It is like a scientific guess . It’s an idea or prediction that scientists make before they do experiments. They use it to guess what might happen and then test it to see if they were right. It’s like a smart guess that helps them learn new things. A scientific hypothesis that has been verified through scientific experiment and research may well be considered a scientific theory .

Etymology: The word “hypothesis” comes from the Greek word “hupothesis,” which means “a basis” or “a supposition.” It combines “hupo” (under) and “thesis” (placing). Synonym:   proposition; assumption; conjecture; postulate Compare:   theory See also: null hypothesis

Characteristics Of Hypothesis

A useful hypothesis must have the following qualities:

• It should never be written as a question.
• You should be able to test it in the real world to see if it’s right or wrong.
• It needs to be clear and exact.
• It should list the factors that will be used to figure out the relationship.
• It should only talk about one thing. You can make a theory in either a descriptive or form of relationship.
• It shouldn’t go against any natural rule that everyone knows is true. Verification will be done well with the tools and methods that are available.
• It should be written in as simple a way as possible so that everyone can understand it.
• It must explain what happened to make an answer necessary.
• It should be testable in a fair amount of time.
• It shouldn’t say different things.

Sources Of Hypothesis

Sources of hypothesis are:

• Patterns of similarity between the phenomenon under investigation and existing hypotheses.
• Insights derived from prior research, concurrent observations, and insights from opposing perspectives.
• The formulations are derived from accepted scientific theories and proposed by researchers.
• In research, it’s essential to consider hypothesis as different subject areas may require various hypotheses (plural form of hypothesis). Researchers also establish a significance level to determine the strength of evidence supporting a hypothesis.
• Individual cognitive processes also contribute to the formation of hypotheses.

One hypothesis is a tentative explanation for an observation or phenomenon. It is based on prior knowledge and understanding of the world, and it can be tested by gathering and analyzing data. Observed facts are the data that are collected to test a hypothesis. They can support or refute the hypothesis.

For example, the hypothesis that “eating more fruits and vegetables will improve your health” can be tested by gathering data on the health of people who eat different amounts of fruits and vegetables. If the people who eat more fruits and vegetables are healthier than those who eat less fruits and vegetables, then the hypothesis is supported.

Hypotheses are essential for scientific inquiry. They help scientists to focus their research, to design experiments, and to interpret their results. They are also essential for the development of scientific theories.

Types Of Hypothesis

In research, you typically encounter two types of hypothesis: the alternative hypothesis (which proposes a relationship between variables) and the null hypothesis (which suggests no relationship).

Simple Hypothesis

It illustrates the association between one dependent variable and one independent variable. For instance, if you consume more vegetables, you will lose weight more quickly. Here, increasing vegetable consumption is the independent variable, while weight loss is the dependent variable.

Complex Hypothesis

It exhibits the relationship between at least two dependent variables and at least two independent variables. Eating more vegetables and fruits results in weight loss, radiant skin, and a decreased risk of numerous diseases, including heart disease.

Directional Hypothesis

It shows that a researcher wants to reach a certain goal. The way the factors are related can also tell us about their nature. For example, four-year-old children who eat well over a time of five years have a higher IQ than children who don’t eat well. This shows what happened and how it happened.

Non-directional Hypothesis

When there is no theory involved, it is used. It is a statement that there is a connection between two variables, but it doesn’t say what that relationship is or which way it goes.

Null Hypothesis

It says something that goes against the theory. It’s a statement that says something is not true, and there is no link between the independent and dependent factors. “H 0 ” represents the null hypothesis.

Associative and Causal Hypothesis

When a change in one variable causes a change in the other variable, this is called the associative hypothesis . The causal hypothesis, on the other hand, says that there is a cause-and-effect relationship between two or more factors.

Examples Of Hypothesis

Examples of simple hypotheses:

• Students who consume breakfast before taking a math test will have a better overall performance than students who do not consume breakfast.
• Students who experience test anxiety before an English examination will get lower scores than students who do not experience test anxiety.
• Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone, is a statement that suggests that drivers who talk on the phone while driving are more likely to make mistakes.

Examples of a complex hypothesis:

• Individuals who consume a lot of sugar and don’t get much exercise are at an increased risk of developing depression.
• Younger people who are routinely exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces, according to a new study.
• Increased levels of air pollution led to higher rates of respiratory illnesses, which in turn resulted in increased costs for healthcare for the affected communities.

Examples of Directional Hypothesis:

• The crop yield will go up a lot if the amount of fertilizer is increased.
• Patients who have surgery and are exposed to more stress will need more time to get better.
• Increasing the frequency of brand advertising on social media will lead to a significant increase in brand awareness among the target audience.

Examples of Non-Directional Hypothesis (or Two-Tailed Hypothesis):

• The test scores of two groups of students are very different from each other.
• There is a link between gender and being happy at work.
• There is a correlation between the amount of caffeine an individual consumes and the speed with which they react.

Examples of a null hypothesis:

• Children who receive a new reading intervention will have scores that are different than students who do not receive the intervention.
• The results of a memory recall test will not reveal any significant gap in performance between children and adults.
• There is not a significant relationship between the number of hours spent playing video games and academic performance.

Examples of Associative Hypothesis:

• There is a link between how many hours you spend studying and how well you do in school.
• Drinking sugary drinks is bad for your health as a whole.
• There is an association between socioeconomic status and access to quality healthcare services in urban neighborhoods.

Functions Of Hypothesis

The research issue can be understood better with the help of a hypothesis, which is why developing one is crucial. The following are some of the specific roles that a hypothesis plays: (Rashid, Apr 20, 2022)

• A hypothesis gives a study a point of concentration. It enlightens us as to the specific characteristics of a study subject we need to look into.
• It instructs us on what data to acquire as well as what data we should not collect, giving the study a focal point .
• The development of a hypothesis improves objectivity since it enables the establishment of a focal point.
• A hypothesis makes it possible for us to contribute to the development of the theory. Because of this, we are in a position to definitively determine what is true and what is untrue .

How will Hypothesis help in the Scientific Method?

• The scientific method begins with observation and inquiry about the natural world when formulating research questions. Researchers can refine their observations and queries into specific, testable research questions with the aid of hypothesis. They provide an investigation with a focused starting point.
• Hypothesis generate specific predictions regarding the expected outcomes of experiments or observations. These forecasts are founded on the researcher’s current knowledge of the subject. They elucidate what researchers anticipate observing if the hypothesis is true.
• Hypothesis direct the design of experiments and data collection techniques. Researchers can use them to determine which variables to measure or manipulate, which data to obtain, and how to conduct systematic and controlled research.
• Following the formulation of a hypothesis and the design of an experiment, researchers collect data through observation, measurement, or experimentation. The collected data is used to verify the hypothesis’s predictions.
• Hypothesis establish the criteria for evaluating experiment results. The observed data are compared to the predictions generated by the hypothesis. This analysis helps determine whether empirical evidence supports or refutes the hypothesis.
• The results of experiments or observations are used to derive conclusions regarding the hypothesis. If the data support the predictions, then the hypothesis is supported. If this is not the case, the hypothesis may be revised or rejected, leading to the formulation of new queries and hypothesis.
• The scientific approach is iterative, resulting in new hypothesis and research issues from previous trials. This cycle of hypothesis generation, testing, and refining drives scientific progress.

Importance Of Hypothesis

• Hypothesis are testable statements that enable scientists to determine if their predictions are accurate. This assessment is essential to the scientific method, which is based on empirical evidence.
• Hypothesis serve as the foundation for designing experiments or data collection techniques. They can be used by researchers to develop protocols and procedures that will produce meaningful results.
• Hypothesis hold scientists accountable for their assertions. They establish expectations for what the research should reveal and enable others to assess the validity of the findings.
• Hypothesis aid in identifying the most important variables of a study. The variables can then be measured, manipulated, or analyzed to determine their relationships.
• Hypothesis assist researchers in allocating their resources efficiently. They ensure that time, money, and effort are spent investigating specific concerns, as opposed to exploring random concepts.
• Testing hypothesis contribute to the scientific body of knowledge. Whether or not a hypothesis is supported, the results contribute to our understanding of a phenomenon.
• Hypothesis can result in the creation of theories. When supported by substantive evidence, hypothesis can serve as the foundation for larger theoretical frameworks that explain complex phenomena.
• Beyond scientific research, hypothesis play a role in the solution of problems in a variety of domains. They enable professionals to make educated assumptions about the causes of problems and to devise solutions.

Research Hypotheses: Did you know that a hypothesis refers to an educated guess or prediction about the outcome of a research study?

It’s like a roadmap guiding researchers towards their destination of knowledge. Just like a compass points north, a well-crafted hypothesis points the way to valuable discoveries in the world of science and inquiry.

Choose the best answer. 

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Further reading.

• RNA-DNA World Hypothesis
• BYJU’S. (2023). Hypothesis. Retrieved 01 Septermber 2023, from https://byjus.com/physics/hypothesis/#sources-of-hypothesis
• Collegedunia. (2023). Hypothesis. Retrieved 1 September 2023, from https://collegedunia.com/exams/hypothesis-science-articleid-7026#d
• Hussain, D. J. (2022). Hypothesis. Retrieved 01 September 2023, from https://mmhapu.ac.in/doc/eContent/Management/JamesHusain/Research%20Hypothesis%20-Meaning,%20Nature%20&%20Importance-Characteristics%20of%20Good%20%20Hypothesis%20Sem2.pdf
• Media, D. (2023). Hypothesis in the Scientific Method. Retrieved 01 September 2023, from https://www.verywellmind.com/what-is-a-hypothesis-2795239#toc-hypotheses-examples
• Rashid, M. H. A. (Apr 20, 2022). Research Methodology. Retrieved 01 September 2023, from https://limbd.org/hypothesis-definitions-functions-characteristics-types-errors-the-process-of-testing-a-hypothesis-hypotheses-in-qualitative-research/#:~:text=Functions%20of%20a%20Hypothesis%3A&text=Specifically%2C%20a%20hypothesis%20serves%20the,providing%20focus%20to%20the%20study.

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Last updated on September 8th, 2023

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10 Scientific Laws and Theories You Really Should Know

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Scientists have many tools available to them when attempting to describe how nature and the universe at large work. Often they reach for laws and theories first. What's the difference? A scientific law can often be reduced to a mathematical statement, such as E = mc²; it's a specific statement based on empirical data, and its truth is generally confined to a certain set of conditions. For example, in the case of E = mc², c refers to the speed of light in a vacuum.

A scientific theory often seeks to synthesize a body of evidence or observations of particular phenomena. It's generally — though by no means always — a grander, testable statement about how nature operates. You can't necessarily reduce a scientific theory to a pithy statement or equation, but it does represent something fundamental about how nature works.

Both laws and theories depend on basic elements of the scientific method, such as generating a hypothesis , testing that premise, finding (or not finding) empirical evidence and coming up with conclusions. Eventually, other scientists must be able to replicate the results if the experiment is destined to become the basis for a widely accepted law or theory.

In this article, we'll look at 10 scientific laws and theories that you might want to brush up on, even if you don't find yourself, say, operating a scanning electron microscope all that frequently. We'll start off with a bang and move on to the basic laws of the universe, before hitting evolution . Finally, we'll tackle some headier material, delving into the realm of quantum physics.

• Big Bang Theory
• Hubble's Law of Cosmic Expansion
• Kepler's Laws of Planetary Motion
• Universal Law of Gravitation
• Newton's Laws of Motion
• Laws of Thermodynamics
• Archimedes' Buoyancy Principle
• Evolution and Natural Selection
• Theory of General Relativity
• Heisenberg's Uncertainty Principle

10: Big Bang Theory

If you're going to know one scientific theory, make it the one that explains how the universe arrived at its present state. Based on research performed by Edwin Hubble, Georges Lemaitre and Albert Einstein, among others, the big bang theory postulates that the universe began almost 14 billion years ago with a massive expansion event. At the time, the universe was confined to a single point, encompassing all of the universe's matter. That original movement continues today, as the universe keeps expanding outward.

The theory of the big bang gained widespread support in the scientific community after Arno Penzias and Robert Wilson discovered cosmic microwave background radiation in 1965. Using radio telescopes, the two astronomers detected cosmic noise, or static, that didn't dissipate over time. Collaborating with Princeton researcher Robert Dicke, the pair confirmed Dicke's hypothesis that the original big bang left behind low-level radiation detectable throughout the universe.

9: Hubble's Law of Cosmic Expansion

Let's stick with Edwin Hubble for a second. While the 1920s roared past and the Great Depression limped by, Hubble was performing groundbreaking astronomical research. Hubble not only proved that there were other galaxies besides the Milky Way , he also discovered that these galaxies were zipping away from our own, a motion he called recession .

In order to quantify the velocity of this galactic movement, Hubble proposed Hubble's Law of Cosmic Expansion , aka Hubble's law, an equation that states: velocity = H × distance . Velocity represents the galaxy's recessional velocity; H is the Hubble constant, or parameter that indicates the rate at which the universe is expanding; and distance is the galaxy's distance from the one with which it's being compared.

Hubble's constant has been calculated at different values over time, but the current accepted value is 70 kilometers/second per megaparsec, the latter being a unit of distance in intergalactic space [source: White ]. For our purposes, that's not so important. What matters most is that Hubble's law provides a concise method for measuring a galaxy's velocity in relation to our own. And perhaps most significantly, the law established that the universe is made up of many galaxies, whose movements trace back to the big bang.

8: Kepler's Laws of Planetary Motion

For centuries, scientists battled with one another and with religious leaders about the planets' orbits, especially about whether they orbited our sun. In the 16th century, Copernicus put forth his controversial concept of a heliocentric solar system, in which the planets revolved around the sun — not Earth. But it would take Johannes Kepler, building on work performed by Tyco Brahe and others, to establish a clear scientific foundation for the planets' movements.

Kepler's three laws of planetary motion — formed in the early 17th century — describe how planets orbit the sun. The first law, sometimes called the law of orbits , states that planets orbit the sun elliptically. The second law, the law of areas , states that a line connecting a planet to the sun covers an equal area over equal periods of time. In other words, if you're measuring the area created by drawing a line from Earth to the sun and tracking Earth's movement over 30 days, the area will be the same no matter where Earth is in its orbit when measurements begin.

The third one, the law of periods , allows us to establish a clear relationship between a planet's orbital period and its distance from the sun. Thanks to this law, we know that a planet relatively close to the sun, like Venus, has a far briefer orbital period than a distant planet, such as Neptune.

7: Universal Law of Gravitation

We may take it for granted now, but more than 300 years ago Sir Isaac Newton proposed a revolutionary idea: that any two objects, no matter their mass, exert gravitational force toward one another. This law is represented by an equation that many high schoolers encounter in physics class. It goes as follows:

F = G × [(m 1 m 2 )/r 2 ]

F is the gravitational force between the two objects, measured in Newtons. M 1 and m 2 are the masses of the two objects, while r is the distance between them. G is the gravitational constant , a number currently calculated to be 6.672 × 10 -11 N m 2 kg -2 [source: Weisstein ].

The benefit of the universal law of gravitation is that it allows us to calculate the gravitational pull between any two objects. This ability is especially useful when scientists are, say, planning to put a satellite in orbit or charting the course of the moon .

6: Newton's Laws of Motion

As long as we're talking about one of the greatest scientists who ever lived, let's move on to Newton's other famous laws. His three laws of motion form an essential component of modern physics. And like many scientific laws, they're rather elegant in their simplicity.

The first of the three laws states an object in motion stays in motion unless acted upon by an outside force. For a ball rolling across the floor, that outside force could be the friction between the ball and the floor, or it could be the toddler that kicks the ball in another direction.

The second law establishes a connection between an object's mass ( m ) and its acceleration ( a ), in the form of the equation F = m × a . F represents force, measured in Newtons. It's also a vector, meaning it has a directional component. Owing to its acceleration, that ball rolling across the floor has a particular vector , a direction in which it's traveling, and it's accounted for in calculating its force.

The third law is rather pithy and should be familiar to you: For every action there is an equal and opposite reaction. That is, for every force applied to an object or surface, that object pushes back with equal force.

5: Laws of Thermodynamics

The British physicist and novelist C.P. Snow once said that a nonscientist who didn't know the second law of thermodynamics was like a scientist who had never read Shakespeare [source: Lambert]. Snow's now-famous statement was meant to emphasize both the importance of thermodynamics and the necessity for nonscientists to learn about it.

Thermodynamics is the study of how energy works in a system, whether it's an engine or Earth's core. It can be reduced to several basic laws, which Snow cleverly summed up as follows [source: Physics Planet]:

• You can't win.
• You can't break even.
• You can't quit the game.

Let's unpack these a bit. By saying you can't win, Snow meant that since matter and energy are conserved, you can't get one without giving up some of the other (i.e., E=mc²). It also means that for an engine to produce work, you have to supply heat, although in anything other than a perfectly closed system, some heat is inevitably lost to the outside world, which then leads to the second law.

The second statement — you can't break even — means that due to ever-increasing entropy , you can't return to the same energy state. Energy concentrated in one place will always flow to places of lower concentration.

Finally, the third law — you can't quit the game — refers to absolute zero, the lowest theoretical temperature possible, measured at zero Kelvin or (minus 273.15 degrees Celsius and minus 459.67 degrees Fahrenheit). When a system reaches absolute zero, molecules stop all movement, meaning that there is no kinetic energy, and entropy reaches its lowest possible value. But in the real world, even in the recesses of space, reaching absolutely zero is impossible — you can only get very close to it.

4: Archimedes' Buoyancy Principle

After he discovered his principle of buoyancy, the ancient Greek scholar Archimedes allegedly yelled out "Eureka!" and ran naked through the city of Syracuse. The discovery was that important. The story goes that Archimedes made his great breakthrough when he noticed the water rise as he got into the tub [source: Quake ].

According to Archimedes' buoyancy principle , the force acting on, or buoying, a submerged or partially submerged object equals the weight of the liquid that the object displaces. This sort of principle has an immense range of applications and is essential to calculations of density, as well as designing submarines and other oceangoing vessels.

3: Evolution and Natural Selection

Now that we've established some of the fundamental concepts of how our universe began and how physics play out in our daily lives, let's turn our attention to the human form and how we got to be the way we are. According to most scientists, all life on Earth has a common ancestor. But in order to produce the immense amount of difference among all living organisms, certain ones had to evolve into distinct species.

In a basic sense, this differentiation occurred through evolution, through descent with modification [source: UCMP ]. Populations of organisms developed different traits, through mechanisms such as mutation. Those with traits that were more beneficial to survival such as, a frog whose brown coloring allows it to be camouflaged in a swamp, were naturally selected for survival; hence the term natural selection .

It's possible to expand upon both of these theories at greater length, but this is the basic, and groundbreaking, discovery that Darwin made in the 19th century: that evolution through natural selection accounts for the tremendous diversity of life on Earth.

2: Theory of General Relativity

Albert Einstein's theory of general relativity remains an important and essential discovery because it permanently altered how we look at the universe. Einstein's major breakthrough was to say that space and time are not absolutes and that gravity is not simply a force applied to an object or mass. Rather, the gravity associated with any mass curves the very space and time (often called space-time) around it.

To conceptualize this, imagine you're traveling across the Earth in a straight line, heading east, starting somewhere in the Northern Hemisphere. After a while, if someone were to pinpoint your position on a map, you'd actually be both east and far south of your original position. That's because Earth is curved. To travel directly east, you'd have to take into account the shape of Earth and angle yourself slightly north. (Think about the difference between a flat paper map and a spherical globe.)

Space is pretty much the same. For example, to the occupants of the shuttle orbiting Earth, it can look like they're traveling on a straight line through space. In reality, the space-time around them is being curved by Earth's gravity (as it would be with any large object with immense gravity such as a planet or a black hole), causing them to both move forward and to appear to orbit Earth.

Einstein's theory had tremendous implications for the future of astrophysics and cosmology. It explained a minor, unexpected anomaly in Mercury's orbit, showed how starlight bends and laid the theoretical foundations for black holes.

1: Heisenberg's Uncertainty Principle

Einstein's broader theory of relativity told us more about how the universe works and helped to lay the foundation for quantum physics, but it also introduced more confusion into theoretical science. In 1927, this sense that the universe's laws were, in some contexts, flexible, led to a groundbreaking discovery by the German scientist Werner Heisenberg.

In postulating his Uncertainty Principle , Heisenberg realized that it was impossible to simultaneously know, with a high level of precision, two properties of a particle. In other words, you can know the position of an electron with a high degree of certainty, but not its momentum and vice versa.

Niels Bohr later made a discovery that helps to explain Heisenberg's principle. Bohr found that an electron has the qualities of both a particle and a wave, a concept known as wave-particle duality , which has become a cornerstone of quantum physics. So when we measure an electron's position, we are treating it as a particle at a specific point in space, with an uncertain wavelength. When we measure its momentum, we are treating it as a wave, meaning we can know the amplitude of its wavelength but not its location.

Keep reading for more science stuff you might like.

Scientific Theory FAQ

What is scientific theory, what is an example of scientific theory, is a scientific law more accurate than a scientific theory, what are the five scientific laws, lots more information, related articles.

• Gravitational Waves! Or the Chirps That Prove Einstein Was Right
• How Newton's Laws of Motion Work
• 10 Scientific Words You're Probably Using Wrong
• How the Scientific Method Works
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Biology Hypothesis

Ai generator.

Delve into the fascinating world of biology with our definitive guide on crafting impeccable hypothesis thesis statements . As the foundation of any impactful biological research, a well-formed hypothesis paves the way for groundbreaking discoveries and insights. Whether you’re examining cellular behavior or large-scale ecosystems, mastering the art of the thesis statement is crucial. Embark on this enlightening journey with us, as we provide stellar examples and invaluable writing advice tailored for budding biologists.

What is a good hypothesis in biology?

A good hypothesis in biology is a statement that offers a tentative explanation for a biological phenomenon, based on prior knowledge or observation. It should be:

• Testable: The hypothesis should be measurable and can be proven false through experiments or observations.
• Clear: It should be stated clearly and without ambiguity.
• Based on Knowledge: A solid hypothesis often stems from existing knowledge or literature in the field.
• Specific: It should clearly define the variables being tested and the expected outcomes.
• Falsifiable: It’s essential that a hypothesis can be disproven. This means there should be a possible result that could indicate the hypothesis is incorrect.

What is an example of a hypothesis statement in biology?

Example: “If a plant is given a higher concentration of carbon dioxide, then it will undergo photosynthesis at an increased rate compared to a plant given a standard concentration of carbon dioxide.”

In this example:

• The independent variable (what’s being changed) is the concentration of carbon dioxide.
• The dependent variable (what’s being measured) is the rate of photosynthesis. The statement proposes a cause-and-effect relationship that can be tested through experimentation.

100 Biology Thesis Statement Examples

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Biology, as the study of life and living organisms, is vast and diverse. Crafting a good thesis statement in this field requires a clear understanding of the topic at hand, capturing the essence of the research aim. From genetics to ecology, from cell biology to animal behavior, the following examples will give you a comprehensive idea about forming succinct biology thesis statements.

Genetics: Understanding the role of the BRCA1 gene in breast cancer susceptibility can lead to targeted treatments.

2. Evolution: The finch populations of the Galápagos Islands provide evidence of natural selection through beak variations in response to food availability.

3. Cell Biology: Mitochondrial dysfunction is a central factor in the onset of age-related neurodegenerative diseases.

4. Ecology: Deforestation in the Amazon directly impacts global carbon dioxide levels, influencing climate change.

5. Human Anatomy: Regular exercise enhances cardiovascular health by improving heart muscle function and reducing arterial plaque.

6. Marine Biology: Coral bleaching events in the Great Barrier Reef correlate strongly with rising sea temperatures.

7. Zoology: Migration patterns of Monarch butterflies are influenced by seasonal changes and available food sources.

8. Botany: The symbiotic relationship between mycorrhizal fungi and plant roots enhances nutrient absorption in poor soil conditions.

9. Microbiology: The overuse of antibiotics in healthcare has accelerated the evolution of antibiotic-resistant bacterial strains.

10. Physiology: High altitude adaptation in certain human populations has led to increased hemoglobin production.

11. Immunology: The role of T-cells in the human immune response is critical in developing effective vaccines against viral diseases.

12. Behavioral Biology: Birdsong variations in sparrows can be attributed to both genetic factors and environmental influences.

13. Developmental Biology: The presence of certain hormones during fetal development dictates the differentiation of sex organs in mammals.

14. Conservation Biology: The rapid decline of bee populations worldwide is directly linked to the use of certain pesticides in agriculture.

15. Molecular Biology: The CRISPR-Cas9 system has revolutionized gene editing techniques, offering potential cures for genetic diseases.

16. Virology: The mutation rate of the influenza virus necessitates annual updates in vaccine formulations.

17. Neurobiology: Neural plasticity in the adult brain can be enhanced through consistent learning and cognitive challenges.

18. Ethology: Elephant herds exhibit complex social structures and matriarchal leadership.

19. Biotechnology: Genetically modified crops can improve yield and resistance but also pose ecological challenges.

20. Environmental Biology: Industrial pollution in freshwater systems disrupts aquatic life and can lead to loss of biodiversity.

21. Neurodegenerative Diseases: Amyloid-beta protein accumulation in the brain is a key marker for Alzheimer’s disease progression.

22. Endocrinology: The disruption of thyroid hormone balance leads to metabolic disorders and weight fluctuations.

23. Bioinformatics: Machine learning algorithms can predict protein structures with high accuracy, advancing drug design.

24. Plant Physiology: The stomatal closure mechanism in plants helps prevent water loss and maintain turgor pressure.

25. Parasitology: The lifecycle of the malaria parasite involves complex interactions between humans and mosquitoes.

26. Molecular Genetics: Epigenetic modifications play a crucial role in gene expression regulation and cell differentiation.

27. Evolutionary Psychology: Human preference for symmetrical faces is a result of evolutionarily advantageous traits.

28. Ecosystem Dynamics: The reintroduction of apex predators in ecosystems restores ecological balance and biodiversity.

29. Epigenetics: Maternal dietary choices during pregnancy can influence the epigenetic profiles of offspring.

30. Biochemistry: Enzyme kinetics in metabolic pathways reveal insights into cellular energy production.

31. Bioluminescence: The role of bioluminescence in deep-sea organisms serves as camouflage and communication.

32. Genetics of Disease: Mutations in the CFTR gene cause cystic fibrosis, leading to severe respiratory and digestive issues.

33. Reproductive Biology: The influence of pheromones on mate selection is a critical aspect of reproductive success in many species.

34. Plant-Microbe Interactions: Rhizobium bacteria facilitate nitrogen fixation in leguminous plants, benefiting both organisms.

35. Comparative Anatomy: Homologous structures in different species provide evidence of shared evolutionary ancestry.

36. Stem Cell Research: Induced pluripotent stem cells hold immense potential for regenerative medicine and disease modeling.

37. Bioethics: Balancing the use of genetic modification in humans with ethical considerations is a complex challenge.

38. Molecular Evolution: The study of orthologous and paralogous genes offers insights into evolutionary relationships.

39. Bioenergetics: ATP synthesis through oxidative phosphorylation is a fundamental process driving cellular energy production.

40. Population Genetics: The Hardy-Weinberg equilibrium model helps predict allele frequencies in populations over time.

41. Animal Communication: The complex vocalizations of whales serve both social bonding and long-distance communication purposes.

42. Biogeography: The distribution of marsupials in Australia and their absence elsewhere highlights the impact of geographical isolation on evolution.

43. Aquatic Ecology: The phenomenon of eutrophication in lakes is driven by excessive nutrient runoff and results in harmful algal blooms.

44. Insect Behavior: The waggle dance of honeybees conveys precise information about the location of food sources to other members of the hive.

45. Microbial Ecology: The gut microbiome’s composition influences host health, metabolism, and immune system development.

46. Evolution of Sex: The Red Queen hypothesis explains the evolution of sexual reproduction as a defense against rapidly evolving parasites.

47. Immunotherapy: Manipulating the immune response to target cancer cells shows promise as an effective cancer treatment strategy.

48. Epigenetic Inheritance: Epigenetic modifications can be passed down through generations, impacting traits and disease susceptibility.

49. Comparative Genomics: Comparing the genomes of different species sheds light on genetic adaptations and evolutionary divergence.

50. Neurotransmission: The dopamine reward pathway in the brain is implicated in addiction and motivation-related behaviors.

51. Microbial Biotechnology: Genetically engineered bacteria can produce valuable compounds like insulin, revolutionizing pharmaceutical production.

52. Bioinformatics: DNA sequence analysis reveals evolutionary relationships between species and uncovers hidden genetic information.

53. Animal Migration: The navigational abilities of migratory birds are influenced by magnetic fields and celestial cues.

54. Human Evolution: The discovery of ancient hominin fossils provides insights into the evolutionary timeline of our species.

55. Cancer Genetics: Mutations in tumor suppressor genes contribute to the uncontrolled growth and division of cancer cells.

56. Aquatic Biomes: Coral reefs, rainforests of the sea, host incredible biodiversity and face threats from climate change and pollution.

57. Genomic Medicine: Personalized treatments based on an individual’s genetic makeup hold promise for more effective healthcare.

58. Molecular Pharmacology: Understanding receptor-ligand interactions aids in the development of targeted drugs for specific diseases.

59. Biodiversity Conservation: Preserving habitat diversity is crucial to maintaining ecosystems and preventing species extinction.

60. Evolutionary Developmental Biology: Comparing embryonic development across species reveals shared genetic pathways and evolutionary constraints.

61. Plant Reproductive Strategies: Understanding the trade-offs between asexual and sexual reproduction in plants sheds light on their evolutionary success.

62. Parasite-Host Interactions: The coevolution of parasites and their hosts drives adaptations and counter-adaptations over time.

63. Genomic Diversity: Exploring genetic variations within populations helps uncover disease susceptibilities and evolutionary history.

64. Ecological Succession: Studying the process of ecosystem recovery after disturbances provides insights into resilience and stability.

65. Conservation Genetics: Genetic diversity assessment aids in formulating effective conservation strategies for endangered species.

66. Neuroplasticity and Learning: Investigating how the brain adapts through synaptic changes improves our understanding of memory and learning.

67. Synthetic Biology: Designing and engineering biological systems offers innovative solutions for medical, environmental, and industrial challenges.

68. Ethnobotany: Documenting the traditional uses of plants by indigenous communities informs both conservation and pharmaceutical research.

69. Ecological Niche Theory: Exploring how species adapt to specific ecological niches enhances our grasp of biodiversity patterns.

70. Ecosystem Services: Quantifying the benefits provided by ecosystems, like pollination and carbon sequestration, supports conservation efforts.

71. Fungal Biology: Investigating mycorrhizal relationships between fungi and plants illuminates nutrient exchange mechanisms.

72. Molecular Clock Hypothesis: Genetic mutations accumulate over time, providing a method to estimate evolutionary divergence dates.

73. Developmental Disorders: Unraveling the genetic and environmental factors contributing to developmental disorders informs therapeutic approaches.

74. Epigenetics and Disease: Epigenetic modifications contribute to the development of diseases like cancer, diabetes, and neurodegenerative disorders.

75. Animal Cognition: Studying cognitive abilities in animals unveils their problem-solving skills, social dynamics, and sensory perceptions.

76. Microbiota-Brain Axis: The gut-brain connection suggests a bidirectional communication pathway influencing mental health and behavior.

77. Neurological Disorders: Neurodegenerative diseases like Parkinson’s and Alzheimer’s have genetic and environmental components that drive their progression.

78. Plant Defense Mechanisms: Investigating how plants ward off pests and pathogens informs sustainable agricultural practices.

79. Conservation Genomics: Genetic data aids in identifying distinct populations and prioritizing conservation efforts for at-risk species.

80. Reproductive Strategies: Comparing reproductive methods in different species provides insights into evolutionary trade-offs and reproductive success.

81. Epigenetics in Aging: Exploring epigenetic changes in the aging process offers insights into longevity and age-related diseases.

82. Antimicrobial Resistance: Understanding the genetic mechanisms behind bacterial resistance to antibiotics informs strategies to combat the global health threat.

83. Plant-Animal Interactions: Investigating mutualistic relationships between plants and pollinators showcases the delicate balance of ecosystems.

84. Adaptations to Extreme Environments: Studying extremophiles reveals the remarkable ways organisms thrive in extreme conditions like deep-sea hydrothermal vents.

85. Genetic Disorders: Genetic mutations underlie numerous disorders like cystic fibrosis, sickle cell anemia, and muscular dystrophy.

86. Conservation Behavior: Analyzing the behavioral ecology of endangered species informs habitat preservation and restoration efforts.

87. Neuroplasticity in Rehabilitation: Harnessing the brain’s ability to rewire itself offers promising avenues for post-injury or post-stroke rehabilitation.

88. Disease Vectors: Understanding how mosquitoes transmit diseases like malaria and Zika virus is critical for disease prevention strategies.

89. Biochemical Pathways: Mapping metabolic pathways in cells provides insights into disease development and potential therapeutic targets.

90. Invasive Species Impact: Examining the effects of invasive species on native ecosystems guides management strategies to mitigate their impact.

91. Molecular Immunology: Studying the intricate immune response mechanisms aids in the development of vaccines and immunotherapies.

92. Plant-Microbe Symbiosis: Investigating how plants form partnerships with beneficial microbes enhances crop productivity and sustainability.

93. Cancer Immunotherapy: Harnessing the immune system to target and eliminate cancer cells offers new avenues for cancer treatment.

94. Evolution of Flight: Analyzing the adaptations leading to the development of flight in birds and insects sheds light on evolutionary innovation.

95. Genomic Diversity in Human Populations: Exploring genetic variations among different human populations informs ancestry, migration, and susceptibility to diseases.

96. Hormonal Regulation: Understanding the role of hormones in growth, reproduction, and homeostasis provides insights into physiological processes.

97. Conservation Genetics in Plant Conservation: Genetic diversity assessment helps guide efforts to conserve rare and endangered plant species.

98. Neuronal Communication: Investigating neurotransmitter systems and synaptic transmission enhances our comprehension of brain function.

99. Microbial Biogeography: Mapping the distribution of microorganisms across ecosystems aids in understanding their ecological roles and interactions.

100. Gene Therapy: Developing methods to replace or repair defective genes offers potential treatments for genetic disorders.

Scientific Hypothesis Statement Examples

This section offers diverse examples of scientific hypothesis statements that cover a range of biological topics. Each example briefly describes the subject matter and the potential implications of the hypothesis.

• Genetic Mutations and Disease: Certain genetic mutations lead to increased susceptibility to autoimmune disorders, providing insights into potential treatment strategies.
• Microplastics in Aquatic Ecosystems: Elevated microplastic levels disrupt aquatic food chains, affecting biodiversity and human health through bioaccumulation.
• Bacterial Quorum Sensing: Inhibition of quorum sensing in pathogenic bacteria demonstrates a potential avenue for novel antimicrobial therapies.
• Climate Change and Phenology: Rising temperatures alter flowering times in plants, impacting pollinator interactions and ecosystem dynamics.
• Neuroplasticity and Learning: The brain’s adaptability facilitates learning through synaptic modifications, elucidating educational strategies for improved cognition.
• CRISPR-Cas9 in Agriculture: CRISPR-engineered crops with enhanced pest resistance showcase a sustainable approach to improving agricultural productivity.
• Invasive Species Impact on Predators: The introduction of invasive prey disrupts predator-prey relationships, triggering cascading effects in terrestrial ecosystems.
• Microbial Contributions to Soil Health: Beneficial soil microbes enhance nutrient availability and plant growth, promoting sustainable agriculture practices.
• Marine Protected Areas: Examining the effectiveness of marine protected areas reveals their role in preserving biodiversity and restoring marine ecosystems.
• Epigenetic Regulation of Cancer: Epigenetic modifications play a pivotal role in cancer development, highlighting potential therapeutic targets for precision medicine.

Testable Hypothesis Statement Examples in Biology

Testability hypothesis is a critical aspect of a hypothesis. These examples are formulated in a way that allows them to be tested through experiments or observations. They focus on cause-and-effect relationships that can be verified or refuted.

• Impact of Light Intensity on Plant Growth: Increasing light intensity accelerates photosynthesis rates and enhances overall plant growth.
• Effect of Temperature on Enzyme Activity: Higher temperatures accelerate enzyme activity up to an optimal point, beyond which denaturation occurs.
• Microbial Diversity in Soil pH Gradients: Soil pH influences microbial composition, with acidic soils favoring certain bacterial taxa over others.
• Predation Impact on Prey Behavior: The presence of predators induces changes in prey behavior, resulting in altered foraging strategies and vigilance levels.
• Chemical Communication in Marine Organisms: Investigating chemical cues reveals the role of allelopathy in competition among marine organisms.
• Social Hierarchy in Animal Groups: Observing animal groups establishes a correlation between social rank and access to resources within the group.
• Effect of Habitat Fragmentation on Pollinator Diversity: Fragmented habitats reduce pollinator species richness, affecting plant reproductive success.
• Dietary Effects on Gut Microbiota Composition: Dietary shifts influence gut microbiota diversity and metabolic functions, impacting host health.
• Hybridization Impact on Plant Fitness: Hybrid plants exhibit varied fitness levels depending on the combination of parent species.
• Human Impact on Coral Bleaching: Analyzing coral reefs under different anthropogenic stresses identifies the main factors driving coral bleaching events.

Scientific Investigation Hypothesis Statement Examples in Biology

This section emphasizes hypotheses that are part of broader scientific investigations. They involve studying complex interactions or phenomena and often contribute to our understanding of larger biological systems.

• Genomic Variation in Human Disease Susceptibility: Genetic analysis identifies variations associated with increased risk of common diseases, aiding personalized medicine.
• Behavioral Responses to Temperature Shifts in Insects: Investigating insect responses to temperature fluctuations reveals adaptation strategies to climate change.
• Endocrine Disruptors and Amphibian Development: Experimental exposure to endocrine disruptors elucidates their role in amphibian developmental abnormalities.
• Microbial Succession in Decomposition: Tracking microbial communities during decomposition uncovers the succession patterns of different decomposer species.
• Gene Expression Patterns in Stress Response: Studying gene expression profiles unveils the molecular mechanisms underlying stress responses in plants.
• Effect of Urbanization on Bird Song Patterns: Urban noise pollution influences bird song frequency and complexity, impacting communication and mate attraction.
• Nutrient Availability and Algal Blooms: Investigating nutrient loading in aquatic systems sheds light on factors triggering harmful algal blooms.
• Host-Parasite Coevolution: Analyzing genetic changes in hosts and parasites over time uncovers coevolutionary arms races and adaptation.
• Ecosystem Productivity and Biodiversity: Linking ecosystem productivity to biodiversity patterns reveals the role of species interactions in ecosystem stability.
• Habitat Preference of Invasive Species: Studying the habitat selection of invasive species identifies factors promoting their establishment and spread.

Hypothesis Statement Examples in Biology Research

These examples are tailored for research hypothesis studies. They highlight hypotheses that drive focused research questions, often leading to specific experimental designs and data collection methods.

• Microbial Community Structure in Human Gut: Investigating microbial diversity and composition unveils the role of gut microbiota in human health.
• Plant-Pollinator Mutualisms: Hypothesizing reciprocal benefits in plant-pollinator interactions highlights the role of coevolution in shaping ecosystems.
• Chemical Defense Mechanisms in Insects: Predicting the correlation between insect feeding behavior and chemical defenses explores natural selection pressures.
• Evolutionary Significance of Mimicry: Examining mimicry in organisms demonstrates its adaptive value in predator-prey relationships and survival.
• Neurological Basis of Mate Choice: Proposing neural mechanisms underlying mate choice behaviors uncovers the role of sensory cues in reproductive success.
• Mycorrhizal Symbiosis Impact on Plant Growth: Investigating mycorrhizal colonization effects on plant biomass addresses nutrient exchange dynamics.
• Social Learning in Primates: Formulating a hypothesis on primate social learning explores the transmission of knowledge and cultural behaviors.
• Effect of Pollution on Fish Behavior: Anticipating altered behaviors due to pollution exposure highlights ecological consequences on aquatic ecosystems.
• Coevolution of Flowers and Pollinators: Hypothesizing mutual adaptations between flowers and pollinators reveals intricate ecological relationships.
• Genetic Basis of Disease Resistance in Plants: Identifying genetic markers associated with disease resistance enhances crop breeding programs.

Prediction Hypothesis Statement Examples in Biology

Predictive simple hypothesis involve making educated guesses about how variables might interact or behave under specific conditions. These examples showcase hypotheses that anticipate outcomes based on existing knowledge.

• Pesticide Impact on Insect Abundance: Predicting decreased insect populations due to pesticide application underscores ecological ramifications.
• Climate Change and Migratory Bird Patterns: Anticipating shifts in migratory routes of birds due to climate change informs conservation strategies.
• Ocean Acidification Effect on Coral Calcification: Predicting reduced coral calcification rates due to ocean acidification unveils threats to coral reefs.
• Disease Spread in Crowded Bird Roosts: Predicting accelerated disease transmission in densely populated bird roosts highlights disease ecology dynamics.
• Eutrophication Impact on Freshwater Biodiversity: Anticipating decreased freshwater biodiversity due to eutrophication emphasizes conservation efforts.
• Herbivore Impact on Plant Species Diversity: Predicting reduced plant diversity in areas with high herbivore pressure elucidates ecosystem dynamics.
• Predator-Prey Population Cycles: Predicting cyclical fluctuations in predator and prey populations showcases the role of trophic interactions.
• Climate Change and Plant Phenology: Anticipating earlier flowering times due to climate change demonstrates the influence of temperature on plant life cycles.
• Antibiotic Resistance in Bacterial Communities: Predicting increased antibiotic resistance due to overuse forewarns the need for responsible antibiotic use.
• Human Impact on Avian Nesting Success: Predicting decreased avian nesting success due to habitat fragmentation highlights conservation priorities.

How to Write a Biology Hypothesis – Step by Step Guide

A hypothesis in biology is a critical component of scientific research that proposes an explanation for a specific biological phenomenon. Writing a well-formulated hypothesis sets the foundation for conducting experiments, making observations, and drawing meaningful conclusions. Follow this step-by-step guide to create a strong biology hypothesis:

1. Identify the Phenomenon: Clearly define the biological phenomenon you intend to study. This could be a question, a pattern, an observation, or a problem in the field of biology.

2. Conduct Background Research: Before formulating a hypothesis, gather relevant information from scientific literature. Understand the existing knowledge about the topic to ensure your hypothesis builds upon previous research.

3. State the Independent and Dependent Variables: Identify the variables involved in the phenomenon. The independent variable is what you manipulate or change, while the dependent variable is what you measure as a result of the changes.

4. Formulate a Testable Question: Based on your background research, create a specific and testable question that addresses the relationship between the variables. This question will guide the formulation of your hypothesis.

5. Craft the Hypothesis: A hypothesis should be a clear and concise statement that predicts the outcome of your experiment or observation. It should propose a cause-and-effect relationship between the independent and dependent variables.

6. Use the “If-Then” Structure: Formulate your hypothesis using the “if-then” structure. The “if” part states the independent variable and the condition you’re manipulating, while the “then” part predicts the outcome for the dependent variable.

7. Make it Falsifiable: A good hypothesis should be testable and capable of being proven false. There should be a way to gather data that either supports or contradicts the hypothesis.

8. Be Specific and Precise: Avoid vague language and ensure that your hypothesis is specific and precise. Clearly define the variables and the expected relationship between them.

9. Revise and Refine: Once you’ve formulated your hypothesis, review it to ensure it accurately reflects your research question and variables. Revise as needed to make it more concise and focused.

10. Seek Feedback: Share your hypothesis with peers, mentors, or colleagues to get feedback. Constructive input can help you refine your hypothesis further.

Tips for Writing a Biology Hypothesis Statement

Writing a biology alternative hypothesis statement requires precision and clarity to ensure that your research is well-structured and testable. Here are some valuable tips to help you create effective and scientifically sound hypothesis statements:

1. Be Clear and Concise: Your hypothesis statement should convey your idea succinctly. Avoid unnecessary jargon or complex language that might confuse your audience.

2. Address Cause and Effect: A hypothesis suggests a cause-and-effect relationship between variables. Clearly state how changes in the independent variable are expected to affect the dependent variable.

3. Use Specific Language: Define your variables precisely. Use specific terms to describe the independent and dependent variables, as well as any conditions or measurements.

4. Follow the “If-Then” Structure: Use the classic “if-then” structure to frame your hypothesis. State the independent variable (if) and the expected outcome (then). This format clarifies the relationship you’re investigating.

5. Make it Testable: Your hypothesis must be capable of being tested through experimentation or observation. Ensure that there is a measurable and observable way to determine if it’s true or false.

6. Avoid Ambiguity: Eliminate vague terms that can be interpreted in multiple ways. Be precise in your language to avoid confusion.

7. Base it on Existing Knowledge: Ground your hypothesis in prior research or existing scientific theories. It should build upon established knowledge and contribute new insights.

8. Predict a Direction: Your hypothesis should predict a specific outcome. Whether you anticipate an increase, decrease, or a difference, your hypothesis should make a clear prediction.

9. Be Focused: Keep your hypothesis statement focused on one specific idea or relationship. Avoid trying to address too many variables or concepts in a single statement.

10. Consider Alternative Explanations: Acknowledge alternative explanations for your observations or outcomes. This demonstrates critical thinking and a thorough understanding of your field.

11. Avoid Value Judgments: Refrain from including value judgments or opinions in your hypothesis. Stick to objective and measurable factors.

12. Be Realistic: Ensure that your hypothesis is plausible and feasible. It should align with what is known about the topic and be achievable within the scope of your research.

13. Refine and Revise: Draft multiple versions of your hypothesis statement and refine them. Discuss and seek feedback from mentors, peers, or advisors to enhance its clarity and precision.

14. Align with Research Goals: Your hypothesis should align with the overall goals of your research project. Make sure it addresses the specific question or problem you’re investigating.

15. Be Open to Revision: As you conduct research and gather data, be open to revising your hypothesis if the evidence suggests a different outcome than initially predicted.

Remember, a well-crafted biology science hypothesis statement serves as the foundation of your research and guides your experimental design and data analysis. It’s essential to invest time and effort in formulating a clear, focused, and testable hypothesis that contributes to the advancement of scientific knowledge.

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How to Write a Great Hypothesis

Hypothesis Definition, Format, Examples, and Tips

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

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

Verywell / Alex Dos Diaz

• The Scientific Method

Hypothesis Format

Falsifiability of a hypothesis.

• Operationalization

Hypothesis Types

Hypotheses examples.

• Collecting Data

A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction about what you expect to happen in a study. It is a preliminary answer to your question that helps guide the research process.

Consider a study designed to examine the relationship between sleep deprivation and test performance. The hypothesis might be: "This study is designed to assess the hypothesis that sleep-deprived people will perform worse on a test than individuals who are not sleep-deprived."

At a Glance

A hypothesis is crucial to scientific research because it offers a clear direction for what the researchers are looking to find. This allows them to design experiments to test their predictions and add to our scientific knowledge about the world. This article explores how a hypothesis is used in psychology research, how to write a good hypothesis, and the different types of hypotheses you might use.

The Hypothesis in the Scientific Method

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

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

The hypothesis is a prediction, but it involves more than a guess. Most of the time, the hypothesis begins with a question which is then explored through background research. At this point, researchers then begin to develop a testable hypothesis.

Unless you are creating an exploratory study, your hypothesis should always explain what you  expect  to happen.

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

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

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

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

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

Elements of a Good Hypothesis

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

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

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

How to Formulate a Good Hypothesis

To form a hypothesis, you should take these steps:

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

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

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

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

The Importance of Operational Definitions

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

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

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

These precise descriptions are important because many things can be measured in various ways. Clearly defining these variables and how they are measured helps ensure that other researchers can replicate your results.

Replicability

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

Replication means repeating an experiment in the same way to produce the same results. By clearly detailing the specifics of how the variables were measured and manipulated, other researchers can better understand the results and repeat the study if needed.

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

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

Hypothesis Checklist

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

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

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

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

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

A few examples of simple hypotheses:

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

Examples of a complex hypothesis include:

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

Examples of a null hypothesis include:

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

Examples of an alternative hypothesis:

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

Collecting Data on Your Hypothesis

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

Descriptive Research Methods

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

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

Experimental Research Methods

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

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

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

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

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

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

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

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

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

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

What is a scientific hypothesis?

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

Hypothesis basics

What makes a hypothesis testable.

• Types of hypotheses
• Hypothesis versus theory

Additional resources

Bibliography.

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

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

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

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

Here are some examples of hypothesis statements:

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

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

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

Types of scientific hypotheses

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

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

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

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

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

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

Scientific theory vs. scientific hypothesis

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

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

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

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

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

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

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

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

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

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

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

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

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Module 1: Introduction to Biology

Experiments and hypotheses, learning outcomes.

• Form a hypothesis and use it to design a scientific experiment

Now we’ll focus on the methods of scientific inquiry. Science often involves making observations and developing hypotheses. Experiments and further observations are often used to test the hypotheses.

A scientific experiment is a carefully organized procedure in which the scientist intervenes in a system to change something, then observes the result of the change. Scientific inquiry often involves doing experiments, though not always. For example, a scientist studying the mating behaviors of ladybugs might begin with detailed observations of ladybugs mating in their natural habitats. While this research may not be experimental, it is scientific: it involves careful and verifiable observation of the natural world. The same scientist might then treat some of the ladybugs with a hormone hypothesized to trigger mating and observe whether these ladybugs mated sooner or more often than untreated ones. This would qualify as an experiment because the scientist is now making a change in the system and observing the effects.

Forming a Hypothesis

When conducting scientific experiments, researchers develop hypotheses to guide experimental design. A hypothesis is a suggested explanation that is both testable and falsifiable. You must be able to test your hypothesis through observations and research, and it must be possible to prove your hypothesis false.

For example, Michael observes that maple trees lose their leaves in the fall. He might then propose a possible explanation for this observation: “cold weather causes maple trees to lose their leaves in the fall.” This statement is testable. He could grow maple trees in a warm enclosed environment such as a greenhouse and see if their leaves still dropped in the fall. The hypothesis is also falsifiable. If the leaves still dropped in the warm environment, then clearly temperature was not the main factor in causing maple leaves to drop in autumn.

In the Try It below, you can practice recognizing scientific hypotheses. As you consider each statement, try to think as a scientist would: can I test this hypothesis with observations or experiments? Is the statement falsifiable? If the answer to either of these questions is “no,” the statement is not a valid scientific hypothesis.

Practice Questions

Determine whether each following statement is a scientific hypothesis.

Air pollution from automobile exhaust can trigger symptoms in people with asthma.

• No. This statement is not testable or falsifiable.
• No. This statement is not testable.
• No. This statement is not falsifiable.
• Yes. This statement is testable and falsifiable.

Natural disasters, such as tornadoes, are punishments for bad thoughts and behaviors.

a: No. This statement is not testable or falsifiable. “Bad thoughts and behaviors” are excessively vague and subjective variables that would be impossible to measure or agree upon in a reliable way. The statement might be “falsifiable” if you came up with a counterexample: a “wicked” place that was not punished by a natural disaster. But some would question whether the people in that place were really wicked, and others would continue to predict that a natural disaster was bound to strike that place at some point. There is no reason to suspect that people’s immoral behavior affects the weather unless you bring up the intervention of a supernatural being, making this idea even harder to test.

Testing a Vaccine

Let’s examine the scientific process by discussing an actual scientific experiment conducted by researchers at the University of Washington. These researchers investigated whether a vaccine may reduce the incidence of the human papillomavirus (HPV). The experimental process and results were published in an article titled, “ A controlled trial of a human papillomavirus type 16 vaccine .”

Preliminary observations made by the researchers who conducted the HPV experiment are listed below:

• Human papillomavirus (HPV) is the most common sexually transmitted virus in the United States.
• There are about 40 different types of HPV. A significant number of people that have HPV are unaware of it because many of these viruses cause no symptoms.
• Some types of HPV can cause cervical cancer.
• About 4,000 women a year die of cervical cancer in the United States.

Practice Question

Researchers have developed a potential vaccine against HPV and want to test it. What is the first testable hypothesis that the researchers should study?

• HPV causes cervical cancer.
• People should not have unprotected sex with many partners.
• People who get the vaccine will not get HPV.
• The HPV vaccine will protect people against cancer.

Experimental Design

You’ve successfully identified a hypothesis for the University of Washington’s study on HPV: People who get the HPV vaccine will not get HPV.

The next step is to design an experiment that will test this hypothesis. There are several important factors to consider when designing a scientific experiment. First, scientific experiments must have an experimental group. This is the group that receives the experimental treatment necessary to address the hypothesis.

The experimental group receives the vaccine, but how can we know if the vaccine made a difference? Many things may change HPV infection rates in a group of people over time. To clearly show that the vaccine was effective in helping the experimental group, we need to include in our study an otherwise similar control group that does not get the treatment. We can then compare the two groups and determine if the vaccine made a difference. The control group shows us what happens in the absence of the factor under study.

However, the control group cannot get “nothing.” Instead, the control group often receives a placebo. A placebo is a procedure that has no expected therapeutic effect—such as giving a person a sugar pill or a shot containing only plain saline solution with no drug. Scientific studies have shown that the “placebo effect” can alter experimental results because when individuals are told that they are or are not being treated, this knowledge can alter their actions or their emotions, which can then alter the results of the experiment.

Moreover, if the doctor knows which group a patient is in, this can also influence the results of the experiment. Without saying so directly, the doctor may show—through body language or other subtle cues—their views about whether the patient is likely to get well. These errors can then alter the patient’s experience and change the results of the experiment. Therefore, many clinical studies are “double blind.” In these studies, neither the doctor nor the patient knows which group the patient is in until all experimental results have been collected.

Both placebo treatments and double-blind procedures are designed to prevent bias. Bias is any systematic error that makes a particular experimental outcome more or less likely. Errors can happen in any experiment: people make mistakes in measurement, instruments fail, computer glitches can alter data. But most such errors are random and don’t favor one outcome over another. Patients’ belief in a treatment can make it more likely to appear to “work.” Placebos and double-blind procedures are used to level the playing field so that both groups of study subjects are treated equally and share similar beliefs about their treatment.

The scientists who are researching the effectiveness of the HPV vaccine will test their hypothesis by separating 2,392 young women into two groups: the control group and the experimental group. Answer the following questions about these two groups.

• This group is given a placebo.
• This group is deliberately infected with HPV.
• This group is given nothing.
• This group is given the HPV vaccine.
• a: This group is given a placebo. A placebo will be a shot, just like the HPV vaccine, but it will have no active ingredient. It may change peoples’ thinking or behavior to have such a shot given to them, but it will not stimulate the immune systems of the subjects in the same way as predicted for the vaccine itself.
• d: This group is given the HPV vaccine. The experimental group will receive the HPV vaccine and researchers will then be able to see if it works, when compared to the control group.

Experimental Variables

A variable is a characteristic of a subject (in this case, of a person in the study) that can vary over time or among individuals. Sometimes a variable takes the form of a category, such as male or female; often a variable can be measured precisely, such as body height. Ideally, only one variable is different between the control group and the experimental group in a scientific experiment. Otherwise, the researchers will not be able to determine which variable caused any differences seen in the results. For example, imagine that the people in the control group were, on average, much more sexually active than the people in the experimental group. If, at the end of the experiment, the control group had a higher rate of HPV infection, could you confidently determine why? Maybe the experimental subjects were protected by the vaccine, but maybe they were protected by their low level of sexual contact.

To avoid this situation, experimenters make sure that their subject groups are as similar as possible in all variables except for the variable that is being tested in the experiment. This variable, or factor, will be deliberately changed in the experimental group. The one variable that is different between the two groups is called the independent variable. An independent variable is known or hypothesized to cause some outcome. Imagine an educational researcher investigating the effectiveness of a new teaching strategy in a classroom. The experimental group receives the new teaching strategy, while the control group receives the traditional strategy. It is the teaching strategy that is the independent variable in this scenario. In an experiment, the independent variable is the variable that the scientist deliberately changes or imposes on the subjects.

Dependent variables are known or hypothesized consequences; they are the effects that result from changes or differences in an independent variable. In an experiment, the dependent variables are those that the scientist measures before, during, and particularly at the end of the experiment to see if they have changed as expected. The dependent variable must be stated so that it is clear how it will be observed or measured. Rather than comparing “learning” among students (which is a vague and difficult to measure concept), an educational researcher might choose to compare test scores, which are very specific and easy to measure.

In any real-world example, many, many variables MIGHT affect the outcome of an experiment, yet only one or a few independent variables can be tested. Other variables must be kept as similar as possible between the study groups and are called control variables . For our educational research example, if the control group consisted only of people between the ages of 18 and 20 and the experimental group contained people between the ages of 30 and 35, we would not know if it was the teaching strategy or the students’ ages that played a larger role in the results. To avoid this problem, a good study will be set up so that each group contains students with a similar age profile. In a well-designed educational research study, student age will be a controlled variable, along with other possibly important factors like gender, past educational achievement, and pre-existing knowledge of the subject area.

What is the independent variable in this experiment?

• Sex (all of the subjects will be female)
• Presence or absence of the HPV vaccine
• Presence or absence of HPV (the virus)

List three control variables other than age.

What is the dependent variable in this experiment?

• Sex (male or female)
• Rates of HPV infection
• Age (years)

Candela Citations

• Revision and adaptation. Authored by : Shelli Carter and Lumen Learning. Provided by : Lumen Learning. License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike
• Scientific Inquiry. Provided by : Open Learning Initiative. Located at : https://oli.cmu.edu/jcourse/workbook/activity/page?context=434a5c2680020ca6017c03488572e0f8 . Project : Introduction to Biology (Open + Free). License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike