ap biology hypothesis examples

1.1 The Science of Biology

Learning objectives.

In this section, you will explore the following questions:

• What are the characteristics shared by the natural sciences?
• What are the steps of the scientific method?

Connection for AP ® courses

Biology is the science that studies living organisms and their interactions with one another and with their environment. The process of science attempts to describe and understand the nature of the universe by rational means. Science has many fields; those fields related to the physical world, including biology, are considered natural sciences. All of the natural sciences follow the laws of chemistry and physics. For example, when studying biology, you must remember living organisms obey the laws of thermodynamics while using free energy and matter from the environment to carry out life processes that are explored in later chapters, such as metabolism and reproduction.

Two types of logical reasoning are used in science: inductive reasoning and deductive reasoning. Inductive reasoning uses particular results to produce general scientific principles. Deductive reasoning uses logical thinking to predict results by applying scientific principles or practices. The scientific method is a step-by-step process that consists of: making observations, defining a problem, posing hypotheses, testing these hypotheses by designing and conducting investigations, and drawing conclusions from data and results. Scientists then communicate their results to the scientific community. Scientific theories are subject to revision as new information is collected.

The content presented in this section supports the Learning Objectives outlined in Big Idea 2 of the AP ® Biology Curriculum Framework. The Learning Objectives merge Essential Knowledge content with one or more of the seven Science Practices. These objectives provide a transparent foundation for the AP ® Biology course, along with inquiry-based laboratory experiences, instructional activities, and AP ® Exam questions.

Teacher Support

Illustrate uses of the scientific method in class. Divide students in groups of four or five and ask them to design experiments to test the existence of connections they have wondered about. Help them decide if they have a working hypothesis that can be tested and falsified. Give examples of hypotheses that are not falsifiable because they are based on subjective assessments. They are neither observable nor measurable. For example, birds like classical music is based on a subjective assessment. Ask if this hypothesis can be modified to become a testable hypothesis. Stress the need for controls and provide examples such as the use of placebos in pharmacology.

Biology is not a collection of facts to be memorized. Biological systems follow the law of physics and chemistry. Give as an example gas laws in chemistry and respiration physiology. Many students come with a 19th century view of natural sciences; each discipline is in its own sphere. Give as an example, bioinformatics which uses organism biology, chemistry, and physics to label DNA with light emitting reporter molecules (Next Generation sequencing). These molecules can then be scanned by light-sensing machinery, allowing huge amounts of information to be gathered on their DNA. Bring to their attention the fact that the analysis of these data is an application of mathematics and computer science.

For more information about next generation sequencing, check out this informative review .

What is biology? In simple terms, biology is the study of life. This is a very broad definition because the scope of biology is vast. Biologists may study anything from the microscopic or submicroscopic view of a cell to ecosystems and the whole living planet ( Figure 1.2 ). Listening to the daily news, you will quickly realize how many aspects of biology are discussed every day. For example, recent news topics include Escherichia coli ( Figure 1.3 ) outbreaks in spinach and Salmonella contamination in peanut butter. On a global scale, many researchers are committed to finding ways to protect the planet, solve environmental issues, and reduce the effects of climate change. All of these diverse endeavors are related to different facets of the discipline of biology.

The Process of Science

Biology is a science, but what exactly is science? What does the study of biology share with other scientific disciplines? Science (from the Latin scientia , meaning “knowledge”) can be defined as knowledge that covers general truths or the operation of general laws, especially when acquired and tested by the scientific method. It becomes clear from this definition that the application of the scientific method plays a major role in science. The scientific method is a method of research with defined steps that include experiments and careful observation.

The steps of the scientific method will be examined in detail later, but one of the most important aspects of this method is the testing of hypotheses by means of repeatable experiments. A hypothesis is a suggested explanation for an event, which can be tested. Although using the scientific method is inherent to science, it is inadequate in determining what science is. This is because it is relatively easy to apply the scientific method to disciplines such as physics and chemistry, but when it comes to disciplines like archaeology, psychology, and geology, the scientific method becomes less applicable as it becomes more difficult to repeat experiments.

These areas of study are still sciences, however. Consider archaeology—even though one cannot perform repeatable experiments, hypotheses may still be supported. For instance, an archaeologist can hypothesize that an ancient culture existed based on finding a piece of pottery. Further hypotheses could be made about various characteristics of this culture, and these hypotheses may be found to be correct or false through continued support or contradictions from other findings. A hypothesis may become a verified theory. A theory is a tested and confirmed explanation for observations or phenomena. Science may be better defined as fields of study that attempt to comprehend the nature of the universe.

Natural Sciences

What would you expect to see in a museum of natural sciences? Frogs? Plants? Dinosaur skeletons? Exhibits about how the brain functions? A planetarium? Gems and minerals? Or, maybe all of the above? Science includes such diverse fields as astronomy, biology, computer sciences, geology, logic, physics, chemistry, and mathematics ( Figure 1.4 ). However, those fields of science related to the physical world and its phenomena and processes are considered natural sciences . Thus, a museum of natural sciences might contain any of the items listed above.

There is no complete agreement when it comes to defining what the natural sciences include, however. For some experts, the natural sciences are astronomy, biology, chemistry, earth science, and physics. Other scholars choose to divide natural sciences into life sciences , which study living things and include biology, and physical sciences , which study nonliving matter and include astronomy, geology, physics, and chemistry. Some disciplines such as biophysics and biochemistry build on both life and physical sciences and are interdisciplinary. Natural sciences are sometimes referred to as “hard science” because they rely on the use of quantitative data; social sciences that study society and human behavior are more likely to use qualitative assessments to drive investigations and findings.

Not surprisingly, the natural science of biology has many branches or subdisciplines. Cell biologists study cell structure and function, while biologists who study anatomy investigate the structure of an entire organism. Those biologists studying physiology, however, focus on the internal functioning of an organism. Some areas of biology focus on only particular types of living things. For example, botanists explore plants, while zoologists specialize in animals.

Scientific Reasoning

One thing is common to all forms of science: an ultimate goal “to know.” Curiosity and inquiry are the driving forces for the development of science. Scientists seek to understand the world and the way it operates. To do this, they use two methods of logical thinking: inductive reasoning and deductive reasoning.

Inductive reasoning is a form of logical thinking that uses related observations to arrive at a general conclusion. This type of reasoning is common in descriptive science. A life scientist such as a biologist makes observations and records them. These data can be qualitative or quantitative, and the raw data can be supplemented with drawings, pictures, photos, or videos. From many observations, the scientist can infer conclusions (inductions) based on evidence. Inductive reasoning involves formulating generalizations inferred from careful observation and the analysis of a large amount of data. Brain studies provide an example. In this type of research, many live brains are observed while people are doing a specific activity, such as viewing images of food. The part of the brain that “lights up” during this activity is then predicted to be the part controlling the response to the selected stimulus, in this case, images of food. The “lighting up” of the various areas of the brain is caused by excess absorption of radioactive sugar derivatives by active areas of the brain. The resultant increase in radioactivity is observed by a scanner. Then, researchers can stimulate that part of the brain to see if similar responses result.

Deductive reasoning or deduction is the type of logic used in hypothesis-based science. In deductive reason, the pattern of thinking moves in the opposite direction as compared to inductive reasoning. Deductive reasoning is a form of logical thinking that uses a general principle or law to predict specific results. From those general principles, a scientist can deduce and predict the specific results that would be valid as long as the general principles are valid. Studies in climate change can illustrate this type of reasoning. For example, scientists may predict that if the climate becomes warmer in a particular region, then the distribution of plants and animals should change. These predictions have been made and tested, and many such changes have been found, such as the modification of arable areas for agriculture, with change based on temperature averages.

Both types of logical thinking are related to the two main pathways of scientific study: descriptive science and hypothesis-based science. Descriptive (or discovery) science , which is usually inductive, aims to observe, explore, and discover, while hypothesis-based science , which is usually deductive, begins with a specific question or problem and a potential answer or solution that can be tested. The boundary between these two forms of study is often blurred, and most scientific endeavors combine both approaches. The fuzzy boundary becomes apparent when thinking about how easily observation can lead to specific questions. For example, a gentleman in the 1940s observed that the burr seeds that stuck to his clothes and his dog’s fur had a tiny hook structure. On closer inspection, he discovered that the burrs’ gripping device was more reliable than a zipper. He eventually developed a company and produced the hook-and-loop fastener often used on lace-less sneakers and athletic braces. Descriptive science and hypothesis-based science are in continuous dialogue.

The Scientific Method

Biologists study the living world by posing questions about it and seeking science-based responses. This approach is common to other sciences as well and is often referred to as the scientific method. The scientific method was used even in ancient times, but it was first documented by England’s Sir Francis Bacon (1561–1626) ( Figure 1.5 ), who set up inductive methods for scientific inquiry. The scientific method is not exclusively used by biologists but can be applied to almost all fields of study as a logical, rational problem-solving method.

The scientific process typically starts with an observation (often a problem to be solved) that leads to a question. Let’s think about a simple problem that starts with an observation and apply the scientific method to solve the problem. One Monday morning, a student arrives at class and quickly discovers that the classroom is too warm. That is an observation that also describes a problem: the classroom is too warm. The student then asks a question: “Why is the classroom so warm?”

Proposing a Hypothesis

Recall that a hypothesis is a suggested explanation that can be tested. To solve a problem, several hypotheses may be proposed. For example, one hypothesis might be, “The classroom is warm because no one turned on the air conditioning.” But there could be other responses to the question, and therefore other hypotheses may be proposed. A second hypothesis might be, “The classroom is warm because there is a power failure, and so the air conditioning doesn’t work.”

Once a hypothesis has been selected, the student can make a prediction. A prediction is similar to a hypothesis but it typically has the format “If . . . then . . . .” For example, the prediction for the first hypothesis might be, “ If the student turns on the air conditioning, then the classroom will no longer be too warm.”

Testing a Hypothesis

A valid hypothesis must be testable. It should also be falsifiable , meaning that it can be disproven by experimental results. Importantly, science does not claim to “prove” anything because scientific understandings are always subject to modification with further information. This step—openness to disproving ideas—is what distinguishes sciences from non-sciences. The presence of the supernatural, for instance, is neither testable nor falsifiable. To test a hypothesis, a researcher will conduct one or more experiments designed to eliminate one or more of the hypotheses. Each experiment will have one or more variables and one or more controls. A variable is any part of the experiment that can vary or change during the experiment. The control group contains every feature of the experimental group except it is not given the manipulation that is hypothesized about. Therefore, if the results of the experimental group differ from the control group, the difference must be due to the hypothesized manipulation, rather than some outside factor. Look for the variables and controls in the examples that follow. To test the first hypothesis, the student would find out if the air conditioning is on. If the air conditioning is turned on but does not work, there should be another reason, and this hypothesis should be rejected. To test the second hypothesis, the student could check if the lights in the classroom are functional. If so, there is no power failure and this hypothesis should be rejected. Each hypothesis should be tested by carrying out appropriate experiments. Be aware that rejecting one hypothesis does not determine whether or not the other hypotheses can be accepted; it simply eliminates one hypothesis that is not valid ( see this figure ). Using the scientific method, the hypotheses that are inconsistent with experimental data are rejected.

While this “warm classroom” example is based on observational results, other hypotheses and experiments might have clearer controls. For instance, a student might attend class on Monday and realize she had difficulty concentrating on the lecture. One observation to explain this occurrence might be, “When I eat breakfast before class, I am better able to pay attention.” The student could then design an experiment with a control to test this hypothesis.

In hypothesis-based science, specific results are predicted from a general premise. This type of reasoning is called deductive reasoning: deduction proceeds from the general to the particular. But the reverse of the process is also possible: sometimes, scientists reach a general conclusion from a number of specific observations. This type of reasoning is called inductive reasoning, and it proceeds from the particular to the general. Inductive and deductive reasoning are often used in tandem to advance scientific knowledge ( see this figure ). In recent years a new approach of testing hypotheses has developed as a result of an exponential growth of data deposited in various databases. Using computer algorithms and statistical analyses of data in databases, a new field of so-called "data research" (also referred to as "in silico" research) provides new methods of data analyses and their interpretation. This will increase the demand for specialists in both biology and computer science, a promising career opportunity.

Science Practice Connection for AP® Courses

Think about it.

Almost all plants use water, carbon dioxide, and energy from the sun to make sugars. Think about what would happen to plants that don’t have sunlight as an energy source or sufficient water. What would happen to organisms that depend on those plants for their own survival?

Make a prediction about what would happen to the organisms living in a rain forest if 50% of its trees were destroyed. How would you test your prediction?

Use this example as a model to make predictions. Emphasize there is no rigid scientific method scheme. Active science is a combination of observations and measurement. Offer the example of ecology where the conventional scientific method is not always applicable because researchers cannot always set experiments in a laboratory and control all the variables.

Possible answers:

Destruction of the rain forest affects the trees, the animals which feed on the vegetation, take shelter on the trees, and large predators which feed on smaller animals. Furthermore, because the trees positively affect rain through massive evaporation and condensation of water vapor, drought follows deforestation.

Tell students a similar experiment on a grand scale may have happened in the past and introduce the next activity “What killed the dinosaurs?”

Some predictions can be made and later observations can support or disprove the prediction.

Ask, “what killed the dinosaurs?” Explain many scientists point to a massive asteroid crashing in the Yucatan peninsula in Mexico. One of the effects was the creation of smoke clouds and debris that blocked the Sun, stamped out many plants and, consequently, brought mass extinction. As is common in the scientific community, many other researchers offer divergent explanations.

Go to this site for a good example of the complexity of scientific method and scientific debate.

Visual Connection

In the example below, the scientific method is used to solve an everyday problem. Order the scientific method steps (numbered items) with the process of solving the everyday problem (lettered items). Based on the results of the experiment, is the hypothesis correct? If it is incorrect, propose some alternative hypotheses.

• The original hypothesis is correct. There is something wrong with the electrical outlet and therefore the toaster doesn’t work.
• The original hypothesis is incorrect. Alternative hypothesis includes that toaster wasn’t turned on.
• The original hypothesis is correct. The coffee maker and the toaster do not work when plugged into the outlet.
• The original hypothesis is incorrect. Alternative hypotheses includes that both coffee maker and toaster were broken.
• All flying birds and insects have wings. Birds and insects flap their wings as they move through the air. Therefore, wings enable flight.
• Insects generally survive mild winters better than harsh ones. Therefore, insect pests will become more problematic if global temperatures increase.
• Chromosomes, the carriers of DNA, are distributed evenly between the daughter cells during cell division. Therefore, each daughter cell will have the same chromosome set as the mother cell.
• Animals as diverse as humans, insects, and wolves all exhibit social behavior. Therefore, social behavior must have an evolutionary advantage.
• 1- Inductive, 2- Deductive, 3- Deductive, 4- Inductive
• 1- Deductive, 2- Inductive, 3- Deductive, 4- Inductive
• 1- Inductive, 2- Deductive, 3- Inductive, 4- Deductive
• 1- Inductive, 2-Inductive, 3- Inductive, 4- Deductive

The scientific method may seem too rigid and structured. It is important to keep in mind that, although scientists often follow this sequence, there is flexibility. Sometimes an experiment leads to conclusions that favor a change in approach; often, an experiment brings entirely new scientific questions to the puzzle. Many times, science does not operate in a linear fashion; instead, scientists continually draw inferences and make generalizations, finding patterns as their research proceeds. Scientific reasoning is more complex than the scientific method alone suggests. Notice, too, that the scientific method can be applied to solving problems that aren’t necessarily scientific in nature.

Two Types of Science: Basic Science and Applied Science

The scientific community has been debating for the last few decades about the value of different types of science. Is it valuable to pursue science for the sake of simply gaining knowledge, or does scientific knowledge only have worth if we can apply it to solving a specific problem or to bettering our lives? This question focuses on the differences between two types of science: basic science and applied science.

Basic science or “pure” science seeks to expand knowledge regardless of the short-term application of that knowledge. It is not focused on developing a product or a service of immediate public or commercial value. The immediate goal of basic science is knowledge for knowledge’s sake, though this does not mean that, in the end, it may not result in a practical application.

In contrast, applied science or “technology,” aims to use science to solve real-world problems, making it possible, for example, to improve a crop yield, find a cure for a particular disease, or save animals threatened by a natural disaster ( Figure 1.8 ). In applied science, the problem is usually defined for the researcher.

Some individuals may perceive applied science as “useful” and basic science as “useless.” A question these people might pose to a scientist advocating knowledge acquisition would be, “What for?” A careful look at the history of science, however, reveals that basic knowledge has resulted in many remarkable applications of great value. Many scientists think that a basic understanding of science is necessary before an application is developed; therefore, applied science relies on the results generated through basic science. Other scientists think that it is time to move on from basic science and instead to find solutions to actual problems. Both approaches are valid. It is true that there are problems that demand immediate attention; however, few solutions would be found without the help of the wide knowledge foundation generated through basic science.

One example of how basic and applied science can work together to solve practical problems occurred after the discovery of DNA structure led to an understanding of the molecular mechanisms governing DNA replication. Strands of DNA, unique in every human, are found in our cells, where they provide the instructions necessary for life. During DNA replication, DNA makes new copies of itself, shortly before a cell divides. Understanding the mechanisms of DNA replication enabled scientists to develop laboratory techniques that are now used to identify genetic diseases. Without basic science, it is unlikely that applied science could exist.

Another example of the link between basic and applied research is the Human Genome Project, a study in which each human chromosome was analyzed and mapped to determine the precise sequence of DNA subunits and the exact location of each gene. (The gene is the basic unit of heredity represented by a specific DNA segment that codes for a functional molecule.) Other less complex organisms have also been studied as part of this project in order to gain a better understanding of human chromosomes. The Human Genome Project ( Figure 1.9 ) relied on basic research carried out with simple organisms and, later, with the human genome. An important end goal eventually became using the data for applied research, seeking cures and early diagnoses for genetically related diseases.

While research efforts in both basic science and applied science are usually carefully planned, it is important to note that some discoveries are made by serendipity , that is, by means of a fortunate accident or a lucky surprise. Penicillin was discovered when biologist Alexander Fleming accidentally left a petri dish of Staphylococcus bacteria open. An unwanted mold grew on the dish, killing the bacteria. The mold turned out to be Penicillium , and a new antibiotic was discovered. Even in the highly organized world of science, luck—when combined with an observant, curious mind—can lead to unexpected breakthroughs.

Reporting Scientific Work

Whether scientific research is basic science or applied science, scientists must share their findings in order for other researchers to expand and build upon their discoveries. Collaboration with other scientists—when planning, conducting, and analyzing results—is important for scientific research. For this reason, important aspects of a scientist’s work are communicating with peers and disseminating results to peers. Scientists can share results by presenting them at a scientific meeting or conference, but this approach can reach only the select few who are present. Instead, most scientists present their results in peer-reviewed manuscripts that are published in scientific journals. Peer-reviewed manuscripts are scientific papers that are reviewed by a scientist’s colleagues, or peers. These colleagues are qualified individuals, often experts in the same research area, who judge whether or not the scientist’s work is suitable for publication. The process of peer review helps to ensure that the research described in a scientific paper or grant proposal is original, significant, logical, and thorough. Grant proposals, which are requests for research funding, are also subject to peer review. Scientists publish their work so other scientists can reproduce their experiments under similar or different conditions to expand on the findings.

A scientific paper is very different from creative writing. Although creativity is required to design experiments, there are fixed guidelines when it comes to presenting scientific results. First, scientific writing must be brief, concise, and accurate. A scientific paper needs to be succinct but detailed enough to allow peers to reproduce the experiments.

The scientific paper consists of several specific sections—introduction, materials and methods, results, and discussion. This structure is sometimes called the “IMRaD” format. There are usually acknowledgment and reference sections as well as an abstract (a concise summary) at the beginning of the paper. There might be additional sections depending on the type of paper and the journal where it will be published; for example, some review papers require an outline.

The introduction starts with brief, but broad, background information about what is known in the field. A good introduction also gives the rationale of the work; it justifies the work carried out and also briefly mentions the end of the paper, where the hypothesis or research question driving the research will be presented. The introduction refers to the published scientific work of others and therefore requires citations following the style of the journal. Using the work or ideas of others without proper citation is considered plagiarism .

The materials and methods section includes a complete and accurate description of the substances used, and the method and techniques used by the researchers to gather data. The description should be thorough enough to allow another researcher to repeat the experiment and obtain similar results, but it does not have to be verbose. This section will also include information on how measurements were made and what types of calculations and statistical analyses were used to examine raw data. Although the materials and methods section gives an accurate description of the experiments, it does not discuss them.

Some journals require a results section followed by a discussion section, but it is more common to combine both. If the journal does not allow the combination of both sections, the results section simply narrates the findings without any further interpretation. The results are presented by means of tables or graphs, but no duplicate information should be presented. In the discussion section, the researcher will interpret the results, describe how variables may be related, and attempt to explain the observations. It is indispensable to conduct an extensive literature search to put the results in the context of previously published scientific research. Therefore, proper citations are included in this section as well.

Finally, the conclusion section summarizes the importance of the experimental findings. While the scientific paper almost certainly answered one or more scientific questions that were stated, any good research should lead to more questions. Therefore, a well-done scientific paper leaves doors open for the researcher and others to continue and expand on the findings.

Review articles do not follow the IMRAD format because they do not present original scientific findings, or primary literature; instead, they summarize and comment on findings that were published as primary literature and typically include extensive reference sections.

This book may not be used in the training of large language models or otherwise be ingested into large language models or generative AI offerings without OpenStax's permission.

Want to cite, share, or modify this book? This book uses the Creative Commons Attribution License and you must attribute OpenStax.

Access for free at https://openstax.org/books/biology-ap-courses/pages/1-introduction

• Authors: Julianne Zedalis, John Eggebrecht
• Publisher/website: OpenStax
• Book title: Biology for AP® Courses
• Publication date: Mar 8, 2018
• Location: Houston, Texas
• Book URL: https://openstax.org/books/biology-ap-courses/pages/1-introduction
• Section URL: https://openstax.org/books/biology-ap-courses/pages/1-1-the-science-of-biology

© Jul 10, 2024 OpenStax. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution License . The OpenStax name, OpenStax logo, OpenStax book covers, OpenStax CNX name, and OpenStax CNX logo are not subject to the Creative Commons license and may not be reproduced without the prior and express written consent of Rice University.

Null hypothesis

Null hypothesis n., plural: null hypotheses [nʌl haɪˈpɒθɪsɪs] Definition: a hypothesis that is valid or presumed true until invalidated by a statistical test

Table of Contents

Null Hypothesis Definition

Null hypothesis is defined as “the commonly accepted fact (such as the sky is blue) and researcher aim to reject or nullify this fact”.

More formally, we can define a null hypothesis as “a statistical theory suggesting that no statistical relationship exists between given observed variables” .

In biology , the null hypothesis is used to nullify or reject a common belief. The researcher carries out the research which is aimed at rejecting the commonly accepted belief.

What Is a Null Hypothesis?

A hypothesis is defined as a theory or an assumption that is based on inadequate evidence. It needs and requires more experiments and testing for confirmation. There are two possibilities that by doing more experiments and testing, a hypothesis can be false or true. It means it can either prove wrong or true (Blackwelder, 1982).

For example, Susie assumes that mineral water helps in the better growth and nourishment of plants over distilled water. To prove this hypothesis, she performs this experiment for almost a month. She watered some plants with mineral water and some with distilled water.

In a hypothesis when there are no statistically significant relationships among the two variables, the hypothesis is said to be a null hypothesis. The investigator is trying to disprove such a hypothesis. In the above example of plants, the null hypothesis is:

There are no statistical relationships among the forms of water that are given to plants for growth and nourishment.

Usually, an investigator tries to prove the null hypothesis wrong and tries to explain a relation and association between the two variables.

An opposite and reverse of the null hypothesis are known as the alternate hypothesis . In the example of plants the alternate hypothesis is:

There are statistical relationships among the forms of water that are given to plants for growth and nourishment.

The example below shows the difference between null vs alternative hypotheses:

Alternate Hypothesis: The world is round Null Hypothesis: The world is not round.

Copernicus and many other scientists try to prove the null hypothesis wrong and false. By their experiments and testing, they make people believe that alternate hypotheses are correct and true. If they do not prove the null hypothesis experimentally wrong then people will not believe them and never consider the alternative hypothesis true and correct.

The alternative and null hypothesis for Susie’s assumption is:

• Null Hypothesis: If one plant is watered with distilled water and the other with mineral water, then there is no difference in the growth and nourishment of these two plants.
• Alternative Hypothesis:  If one plant is watered with distilled water and the other with mineral water, then the plant with mineral water shows better growth and nourishment.

The null hypothesis suggests that there is no significant or statistical relationship. The relation can either be in a single set of variables or among two sets of variables.

Most people consider the null hypothesis true and correct. Scientists work and perform different experiments and do a variety of research so that they can prove the null hypothesis wrong or nullify it. For this purpose, they design an alternate hypothesis that they think is correct or true. The null hypothesis symbol is H 0 (it is read as H null or H zero ).

Why is it named the “Null”?

The name null is given to this hypothesis to clarify and explain that the scientists are working to prove it false i.e. to nullify the hypothesis. Sometimes it confuses the readers; they might misunderstand it and think that statement has nothing. It is blank but, actually, it is not. It is more appropriate and suitable to call it a nullifiable hypothesis instead of the null hypothesis.

Why do we need to assess it? Why not just verify an alternate one?

In science, the scientific method is used. It involves a series of different steps. Scientists perform these steps so that a hypothesis can be proved false or true. Scientists do this to confirm that there will be any limitation or inadequacy in the new hypothesis. Experiments are done by considering both alternative and null hypotheses, which makes the research safe. It gives a negative as well as a bad impact on research if a null hypothesis is not included or a part of the study. It seems like you are not taking your research seriously and not concerned about it and just want to impose your results as correct and true if the null hypothesis is not a part of the study.

Development of the Null

In statistics, firstly it is necessary to design alternate and null hypotheses from the given problem. Splitting the problem into small steps makes the pathway towards the solution easier and less challenging. how to write a null hypothesis?

Writing a null hypothesis consists of two steps:

• Firstly, initiate by asking a question.
• Secondly, restate the question in such a way that it seems there are no relationships among the variables.

In other words, assume in such a way that the treatment does not have any effect.

The usual recovery duration after knee surgery is considered almost 8 weeks.

A researcher thinks that the recovery period may get elongated if patients go to a physiotherapist for rehabilitation twice per week, instead of thrice per week, i.e. recovery duration reduces if the patient goes three times for rehabilitation instead of two times.

Step 1: Look for the problem in the hypothesis. The hypothesis either be a word or can be a statement. In the above example the hypothesis is:

“The expected recovery period in knee rehabilitation is more than 8 weeks”

Step 2: Make a mathematical statement from the hypothesis. Averages can also be represented as μ, thus the null hypothesis formula will be.

In the above equation, the hypothesis is equivalent to H1, the average is denoted by μ and > that the average is greater than eight.

Step 3: Explain what will come up if the hypothesis does not come right i.e., the rehabilitation period may not proceed more than 08 weeks.

There are two options: either the recovery will be less than or equal to 8 weeks.

H 0 : μ ≤ 8

In the above equation, the null hypothesis is equivalent to H 0 , the average is denoted by μ and ≤ represents that the average is less than or equal to eight.

What will happen if the scientist does not have any knowledge about the outcome?

Problem: An investigator investigates the post-operative impact and influence of radical exercise on patients who have operative procedures of the knee. The chances are either the exercise will improve the recovery or will make it worse. The usual time for recovery is 8 weeks.

Step 1: Make a null hypothesis i.e. the exercise does not show any effect and the recovery time remains almost 8 weeks.

H 0 : μ = 8

In the above equation, the null hypothesis is equivalent to H 0 , the average is denoted by μ, and the equal sign (=) shows that the average is equal to eight.

Step 2: Make the alternate hypothesis which is the reverse of the null hypothesis. Particularly what will happen if treatment (exercise) makes an impact?

In the above equation, the alternate hypothesis is equivalent to H1, the average is denoted by μ and not equal sign (≠) represents that the average is not equal to eight.

Significance Tests

To get a reasonable and probable clarification of statistics (data), a significance test is performed. The null hypothesis does not have data. It is a piece of information or statement which contains numerical figures about the population. The data can be in different forms like in means or proportions. It can either be the difference of proportions and means or any odd ratio.

The following table will explain the symbols:

P-value is the chief statistical final result of the significance test of the null hypothesis.

• P-value = Pr(data or data more extreme | H 0 true)
• | = “given”
• Pr = probability
• H 0 = the null hypothesis

The first stage of Null Hypothesis Significance Testing (NHST) is to form an alternate and null hypothesis. By this, the research question can be briefly explained.

Null Hypothesis = no effect of treatment, no difference, no association Alternative Hypothesis = effective treatment, difference, association

When to reject the null hypothesis?

Researchers will reject the null hypothesis if it is proven wrong after experimentation. Researchers accept null hypothesis to be true and correct until it is proven wrong or false. On the other hand, the researchers try to strengthen the alternate hypothesis. The binomial test is performed on a sample and after that, a series of tests were performed (Frick, 1995).

Step 1: Evaluate and read the research question carefully and consciously and make a null hypothesis. Verify the sample that supports the binomial proportion. If there is no difference then find out the value of the binomial parameter.

Show the null hypothesis as:

H 0 :p= the value of p if H 0 is true

To find out how much it varies from the proposed data and the value of the null hypothesis, calculate the sample proportion.

Step 2: In test statistics, find the binomial test that comes under the null hypothesis. The test must be based on precise and thorough probabilities. Also make a list of pmf that apply, when the null hypothesis proves true and correct.

When H 0 is true, X~b(n, p)

N = size of the sample

P = assume value if H 0 proves true.

Step 3: Find out the value of P. P-value is the probability of data that is under observation.

Rise or increase in the P value = Pr(X ≥ x)

X = observed number of successes

P value = Pr(X ≤ x).

Step 4: Demonstrate the findings or outcomes in a descriptive detailed way.

• Sample proportion
• The direction of difference (either increases or decreases)

Perceived Problems With the Null Hypothesis

Variable or model selection and less information in some cases are the chief important issues that affect the testing of the null hypothesis. Statistical tests of the null hypothesis are reasonably not strong. There is randomization about significance. (Gill, 1999) The main issue with the testing of the null hypothesis is that they all are wrong or false on a ground basis.

There is another problem with the a-level . This is an ignored but also a well-known problem. The value of a-level is without a theoretical basis and thus there is randomization in conventional values, most commonly 0.q, 0.5, or 0.01. If a fixed value of a is used, it will result in the formation of two categories (significant and non-significant) The issue of a randomized rejection or non-rejection is also present when there is a practical matter which is the strong point of the evidence related to a scientific matter.

The P-value has the foremost importance in the testing of null hypothesis but as an inferential tool and for interpretation, it has a problem. The P-value is the probability of getting a test statistic at least as extreme as the observed one.

The main point about the definition is: Observed results are not based on a-value

Moreover, the evidence against the null hypothesis was overstated due to unobserved results. A-value has importance more than just being a statement. It is a precise statement about the evidence from the observed results or data. Similarly, researchers found that P-values are objectionable. They do not prefer null hypotheses in testing. It is also clear that the P-value is strictly dependent on the null hypothesis. It is computer-based statistics. In some precise experiments, the null hypothesis statistics and actual sampling distribution are closely related but this does not become possible in observational studies.

Some researchers pointed out that the P-value is depending on the sample size. If the true and exact difference is small, a null hypothesis even of a large sample may get rejected. This shows the difference between biological importance and statistical significance. (Killeen, 2005)

Another issue is the fix a-level, i.e., 0.1. On the basis, if a-level a null hypothesis of a large sample may get accepted or rejected. If the size of simple is infinity and the null hypothesis is proved true there are still chances of Type I error. That is the reason this approach or method is not considered consistent and reliable. There is also another problem that the exact information about the precision and size of the estimated effect cannot be known. The only solution is to state the size of the effect and its precision.

Null Hypothesis Examples

Here are some examples:

Example 1: Hypotheses with One Sample of One Categorical Variable

Among all the population of humans, almost 10% of people prefer to do their task with their left hand i.e. left-handed. Let suppose, a researcher in the Penn States says that the population of students at the College of Arts and Architecture is mostly left-handed as compared to the general population of humans in general public society. In this case, there is only a sample and there is a comparison among the known population values to the population proportion of sample value.

• Research Question: Do artists more expected to be left-handed as compared to the common population persons in society?
• Response Variable: Sorting the student into two categories. One category has left-handed persons and the other category have right-handed persons.
• Form Null Hypothesis: Arts and Architecture college students are no more predicted to be lefty as compared to the common population persons in society (Lefty students of Arts and Architecture college population is 10% or p= 0.10)

Example 2: Hypotheses with One Sample of One Measurement Variable

A generic brand of antihistamine Diphenhydramine making medicine in the form of a capsule, having a 50mg dose. The maker of the medicines is concerned that the machine has come out of calibration and is not making more capsules with the suitable and appropriate dose.

• Research Question: Does the statistical data recommended about the mean and average dosage of the population differ from 50mg?
• Response Variable: Chemical assay used to find the appropriate dosage of the active ingredient.
• Null Hypothesis: Usually, the 50mg dosage of capsules of this trade name (population average and means dosage =50 mg).

Example 3: Hypotheses with Two Samples of One Categorical Variable

Several people choose vegetarian meals on a daily basis. Typically, the researcher thought that females like vegetarian meals more than males.

• Research Question: Does the data recommend that females (women) prefer vegetarian meals more than males (men) regularly?
• Response Variable: Cataloguing the persons into vegetarian and non-vegetarian categories. Grouping Variable: Gender
• Null Hypothesis: Gender is not linked to those who like vegetarian meals. (Population percent of women who eat vegetarian meals regularly = population percent of men who eat vegetarian meals regularly or p women = p men).

Example 4: Hypotheses with Two Samples of One Measurement Variable

Nowadays obesity and being overweight is one of the major and dangerous health issues. Research is performed to confirm that a low carbohydrates diet leads to faster weight loss than a low-fat diet.

• Research Question: Does the given data recommend that usually, a low-carbohydrate diet helps in losing weight faster as compared to a low-fat diet?
• Response Variable: Weight loss (pounds)
• Explanatory Variable: Form of diet either low carbohydrate or low fat
• Null Hypothesis: There is no significant difference when comparing the mean loss of weight of people using a low carbohydrate diet to people using a diet having low fat. (population means loss of weight on a low carbohydrate diet = population means loss of weight on a diet containing low fat).

Example 5: Hypotheses about the relationship between Two Categorical Variables

A case-control study was performed. The study contains nonsmokers, stroke patients, and controls. The subjects are of the same occupation and age and the question was asked if someone at their home or close surrounding smokes?

• Research Question: Did second-hand smoke enhance the chances of stroke?
• Variables: There are 02 diverse categories of variables. (Controls and stroke patients) (whether the smoker lives in the same house). The chances of having a stroke will be increased if a person is living with a smoker.
• Null Hypothesis: There is no significant relationship between a passive smoker and stroke or brain attack. (odds ratio between stroke and the passive smoker is equal to 1).

Example 6: Hypotheses about the relationship between Two Measurement Variables

A financial expert observes that there is somehow a positive and effective relationship between the variation in stock rate price and the quantity of stock bought by non-management employees

• Response variable- Regular alteration in price
• Explanatory Variable- Stock bought by non-management employees
• Null Hypothesis: The association and relationship between the regular stock price alteration ($) and the daily stock-buying by non-management employees ($) = 0.

Example 7: Hypotheses about comparing the relationship between Two Measurement Variables in Two Samples

• Research Question: Is the relation between the bill paid in a restaurant and the tip given to the waiter, is linear? Is this relation different for dining and family restaurants?
• Explanatory Variable- total bill amount
• Response Variable- the amount of tip
• Null Hypothesis: The relationship and association between the total bill quantity at a family or dining restaurant and the tip, is the same.

Try to answer the quiz below to check what you have learned so far about the null hypothesis.

Choose the best answer. 

Send Your Results (Optional)

• Blackwelder, W. C. (1982). “Proving the null hypothesis” in clinical trials. Controlled Clinical Trials , 3(4), 345–353.
• Frick, R. W. (1995). Accepting the null hypothesis. Memory & Cognition, 23(1), 132–138.
• Gill, J. (1999). The insignificance of null hypothesis significance testing. Political Research Quarterly , 52(3), 647–674.
• Killeen, P. R. (2005). An alternative to null-hypothesis significance tests. Psychological Science, 16(5), 345–353.

©BiologyOnline.com. Content provided and moderated by Biology Online Editors.

Last updated on June 16th, 2022

You will also like...

Human reproduction.

Humans are capable of only one mode of reproduction, i.e. sexual reproduction. Haploid sex cells (gametes) are produced ..

Amphibians & Early Reptiles

Obtaining air outside an aquatic environment required species to acquire suitable adaptations, and this was the case of ..

Independent Assortment and Crossing Over

This tutorial describes the independent assortment of chromosomes and crossing over as important events in meiosis. Read..

Freshwater Community Energy Relationships – Producers & Consumers

This tutorial looks at the relationship between organisms. It also explores how energy is passed on in the food chain an..

Sleep and Dreams – Neurology

While learning and intelligence are associated with the functions of a conscious mind, sleep and dreams are activities o..

Birth of a Human Baby

Following nine months inside the mother's womb is the birth of the baby. Know the different stages of the birthing proce..

Related Articles...

No related articles found

• Science Notes Posts
• Contact Science Notes
• Todd Helmenstine Biography
• Anne Helmenstine Biography
• Free Printable Periodic Tables (PDF and PNG)
• Periodic Table Wallpapers
• Interactive Periodic Table
• Periodic Table Posters
• Science Experiments for Kids
• How to Grow Crystals
• Chemistry Projects
• Fire and Flames Projects
• Holiday Science
• Chemistry Problems With Answers
• Physics Problems
• Unit Conversion Example Problems
• Chemistry Worksheets
• Biology Worksheets
• Periodic Table Worksheets
• Physical Science Worksheets
• Science Lab Worksheets
• My Amazon Books

Hypothesis Examples

A hypothesis is a prediction of the outcome of a test. It forms the basis for designing an experiment in the scientific method . A good hypothesis is testable, meaning it makes a prediction you can check with observation or experimentation. Here are different hypothesis examples.

Null Hypothesis Examples

The null hypothesis (H 0 ) is also known as the zero-difference or no-difference hypothesis. It predicts that changing one variable ( independent variable ) will have no effect on the variable being measured ( dependent variable ). Here are null hypothesis examples:

• Plant growth is unaffected by temperature.
• If you increase temperature, then solubility of salt will increase.
• Incidence of skin cancer is unrelated to ultraviolet light exposure.
• All brands of light bulb last equally long.
• Cats have no preference for the color of cat food.
• All daisies have the same number of petals.

Sometimes the null hypothesis shows there is a suspected correlation between two variables. For example, if you think plant growth is affected by temperature, you state the null hypothesis: “Plant growth is not affected by temperature.” Why do you do this, rather than say “If you change temperature, plant growth will be affected”? The answer is because it’s easier applying a statistical test that shows, with a high level of confidence, a null hypothesis is correct or incorrect.

Research Hypothesis Examples

A research hypothesis (H 1 ) is a type of hypothesis used to design an experiment. This type of hypothesis is often written as an if-then statement because it’s easy identifying the independent and dependent variables and seeing how one affects the other. If-then statements explore cause and effect. In other cases, the hypothesis shows a correlation between two variables. Here are some research hypothesis examples:

• If you leave the lights on, then it takes longer for people to fall asleep.
• If you refrigerate apples, they last longer before going bad.
• If you keep the curtains closed, then you need less electricity to heat or cool the house (the electric bill is lower).
• If you leave a bucket of water uncovered, then it evaporates more quickly.
• Goldfish lose their color if they are not exposed to light.
• Workers who take vacations are more productive than those who never take time off.

Is It Okay to Disprove a Hypothesis?

Yes! You may even choose to write your hypothesis in such a way that it can be disproved because it’s easier to prove a statement is wrong than to prove it is right. In other cases, if your prediction is incorrect, that doesn’t mean the science is bad. Revising a hypothesis is common. It demonstrates you learned something you did not know before you conducted the experiment.

Test yourself with a Scientific Method Quiz .

• Mellenbergh, G.J. (2008). Chapter 8: Research designs: Testing of research hypotheses. In H.J. Adèr & G.J. Mellenbergh (eds.), Advising on Research Methods: A Consultant’s Companion . Huizen, The Netherlands: Johannes van Kessel Publishing.
• Popper, Karl R. (1959). The Logic of Scientific Discovery . Hutchinson & Co. ISBN 3-1614-8410-X.
• Schick, Theodore; Vaughn, Lewis (2002). How to think about weird things: critical thinking for a New Age . Boston: McGraw-Hill Higher Education. ISBN 0-7674-2048-9.
• Tobi, Hilde; Kampen, Jarl K. (2018). “Research design: the methodology for interdisciplinary research framework”. Quality & Quantity . 52 (3): 1209–1225. doi: 10.1007/s11135-017-0513-8

Related Posts

Excel at Science

• May 9, 2020

How to Answer Experiment Questions on AP Biology FRQ

Updated: Sep 22, 2023

On the AP Biology exam, the first section is multiple-choice and the second section is a set of 8 FRQs (free response questions), in which you may be given an experiment setup or asked to design an experiment yourself. Many students find the FRQs challenging because experimental design is not a specific chapter in the AP Biology textbook.

In order to answer these questions well, you need to put on your scientist’s hat and think about it as if you were running the experiment. The best way to demonstrate this is to walk through some examples of experiments. First, we will discuss the guidelines and terminology used for designing and running experiments in biology.

An experiment should always be based on a hypothesis, something that you believe might be true and that you want to test. If there is no hypothesis, there is no purpose for the experiment. Often, the hypothesis is an association between a factor and a result of interest. Some examples are:

Sunlight and plant growth

Mutation in bacteria and resistance to an antibiotic

A particular drug and decreased blood pressure

Soil acidity and flower color

Let’s take the second example, a particular mutation in bacteria and resistance to a specific antibiotic. There are so many different aspects of bacteria and the environment they live in. How can we determine that one particular trait (in this case, a mutated gene) is responsible for antibiotic resistance?

This is why scientists use controlled environments for their experiments. They can control for all factors ( keep them the same) across all experimental groups except the suspected factor, the gene mutation. Each experimental group has a different treatment or condition. In a control group, there is no special treatment. The control group serves as a baseline to compare the other groups to. The diagram below illustrates this:

Notice that all other factors (bacterial strain, concentration of nutrients, concentration of antibiotic added, etc.) are kept the same.

Another term often used in experimentation is null hypothesis . This is different from the scientific hypothesis! Many students get confused by that. The null hypothesis is more of a statistics term and it states that there will be no significant difference observed among the different experimental groups. Scientists usually hope to reject the null hypothesis , which means they do observe a real difference, supporting their scientific hypothesis . This will all become more clear when we walk through some examples.

Example Problems:

2017 FRQ - #2 Bees and Caffeine Experiment

This question involves an experiment about bees and the nectar they encounter while pollinating flowers. The scientists want to understand the role of caffeine on the bees’ memory.

The question gives a table showing the results of the experiment, shown below. It includes a control group and test group (caffeine). It also shows the probability of the bees returning to a recently visited nectar source. This probability is used to represent the bees’ short-term and long-term memory.

As you read through the question and think about the experiment, you should consider the set of questions below. Just consider them, no need to write them down. They will help you plan out your responses to the actual problem:

What are these scientists testing in this experiment? In other words, what is their scientific hypothesis ?

What is the independent and dependent variable?

What is the difference between the control and test group? What’s the purpose of the control group? Note that sometimes there is more than one test group. Here, we only have one, which is the caffeine treatment group.

What is the null hypothesis ?

How could the experimental data be represented graphically?

What do the +/- values mean in each of the data cells?

If you are able to answer all those questions, you will have no trouble with this problem. So let’s answer them:

The scientific hypothesis is that exposure to caffeine is associated with the bees’ memory.

The independent variable is the treatment, which is exposure to caffeine. The dependent variable is what is impacted. Here, that is the bees’ memory.

The control group is exposed to no caffeine, while the treatment group is exposed to caffeine in the nectar. The control group serves as a baseline to compare the treatment group to. If we hypothesize that caffeine has a negative impact on memory, then the probability of revisiting the nectar source should be higher for the treatment compared to the control.

The null hypothesis states that there is no significant difference in memory between the control and treatment groups. Any difference observed would be due to chance. To support the scientific hypothesis, scientists need the data to reject the null hypothesis.

The data here should be represented by a bar graph. There will be two bars, one for control and one for treatment. There should also be error bars because the standard errors are included in the data. The graph would look something like this:

2019 FRQ - #2 Ecological Relationship Between Two Protists

This question is about an experiment that investigates the ecological relationship between two protists. Are they competing for the same food? Does one predate on the other? Or do they live together in harmony and use different resources? That is what the scientists want to know.

The data collected in the experiment is given in the question, shown below.

Let’s answer the same list of questions again to really understand the experiment.

The scientific question being tested is: what kind of ecological relationship do protist species A and B have?

The independent variable is the treatment, which is the two species living together. The dependent variable is the population size of each species over time.

The control group is the species grown separately. The test group is the species grown together.

The null hypothesis states that there is no significant difference in population size between the control and treatment groups at each time point. Any difference observed would be due to chance.

The data here should be represented by a line graph, since we have time as a factor. Time should be on the x-axis -- this is almost always the case. There will be two lines, one for control and one for treatment. The graph would look something like this:

Want to improve your AP Bio free response scores, fast?

Check out the AP Bio Practice Portal , which is our popular vault of 300+ AP-style MCQ and FRQ problem sets with answers and explanations for every question. Don't waste any more time Googling practice problems or answers - try it out now!

Try the Practice Portal >

Recent posts.

How to Study for AP Biology Finals: Tactical Strategies for Success

How to Interpret Diagrams and Graphs on AP Biology Exams

How to Get a 5 on the AP Biology Exam: A Comprehensive Study Guide

How to Write an AP® Biology Lab Report

Writing a good lab report starts with taking smart steps when you conduct the lab. You should take notes about your methods, keep careful track of your data, and think critically during the lab about what could have been improved or done differently. If you are allowed to, taking pictures of your experimental setup is a good idea to make sure you are accurate in your descriptions when you write your lab report for your AP® Biology class. If photos are not allowed, consider making sketches in your lab notebook of any complicated setups. Don’t wait too long after you perform the lab to write the lab report, so that the information is still fresh in your mind.

Individual teachers vary in their specific requirements for AP Biology lab report formats, so make sure you pay attention to the instructions your teacher gives you. If you have any questions or if there is something you don’t understand, ask your teacher! They are there to help you. After you write your lab report, it is important to read over it and check for spelling or grammatical errors, which are not acceptable in scientific writing. Note that, with the exception of the title and materials list, you should always use complete sentences in your lab report.

Below are some general guidelines on how to write an AP Biology lab report. With this goal in mind, a great lab report is both concise and descriptive and contains the following sections:

The title of your lab report should be as specific as possible (i.e., “Lab 1” is not a specific title). Oftentimes, you can follow the model of “ The Effect of X on Y .” For example, in an experiment where you tested different types of fertilizer and how well they made potato plants grow, a good title would be “The Effect of Fertilizer Type on Growth in Potato Plants.”

You don’t need to go into too much detail in the title; that’s what the other sections are for. As an example, “ The Effect of Organic and Synthetic Fertilizers on Growth in Eighteen Potato Plants ” is too much information. You should be as concise as possible while still giving your reader a good idea of what type of experiment you performed and what they should expect from the overall report.

Although not all teachers will require an abstract, this section is good practice for reading and writing real scientific articles. This section should give a brief summary (typically less than 100 words) of the entire experiment and analysis. You should cover what is being studied, your hypothesis, and a summary of the results. You should also include a concluding statement of the big takeaways from the experiment.

Introduction/Background

This section of your lab report should provide your reader with any background information they will need to understand your experiment. You should introduce the purpose of the experiment in this section of the lab report so that it is clear why the lab experiment was performed.

In this portion of your lab report, you will state your hypothesis, or testable statement. Your hypothesis is generally written in an “If…, then…” format (eg, “If organic fertilizer is better for plant growth than synthetic fertilizer, then potato plants will grow taller when exposed to organic fertilizer than when exposed to synthetic fertilizer”). You should include any reasoning that went into the formation of your hypothesis.

For example, if you hypothesize that organic fertilizer will result in better potato plant growth than synthetic fertilizer, why do you think that? Generally, you need to provide a brief definition of key terms you use in this section when they are introduced.

Materials and Methods

In this portion of your lab report, you will go into detail about the materials you used in your experiment and what steps you performed. Typically, this section involves a bulleted list of all materials used and their quantities. However, different teachers may have different preferences for how the materials you used are communicated in your lab report. Remember to include all materials you used; for example, don’t forget items such as soil and water in a plant growth experiment.

In addition to the materials list, you will detail each step you took to complete your experiment. The goal of writing this section in any scientific field is to make your results reproducible by other scientists, which would make your experiment accurate and valid in the eyes of the scientific community.

Employing meticulousness in writing this section is preparing you for what to expect in the real world of science. With this in mind, make sure you mention all the variables that were controlled, along with the independent and dependent variables. In addition, you should use the past tense when writing this section, as your materials and methods are a description of an experiment that you have already performed. For example, you would write, “the height of each potato plant was measured daily”, not “measure the height of each potato plant daily.”

The results you obtained during your experiment are displayed in this section of your lab report. Usually, this will be in the form of table(s) and/or graph(s), depending on your experiment. Think about your experiment and results, and how you can best depict them visually.

When creating tables and graphs, make sure each one is clear and easy to follow and that they each have a descriptive title. Consider whether you should include averages for experiments in which multiple trials were performed. When you display numerical figures, units should always be included. If your lab report contains a graph, make sure to label both the X and Y axes appropriately and to include a key or legend if necessary. In some labs, you will perform statistical analyses; make sure to include this here if it was part of your experiment.

The statistical analyses, graphing tasks, and tabular data production required for your AP Biology lab report are directly tied to the science practices you will be tested on during the AP Biology exam, as shown in our AP Biology Study Guide and Materials article. So make sure you put your best effort into learning and mastering the skill set of representing scientific data in a visual manner and using statistics-based reasoning.

Often, results that do not support your hypothesis are just as valuable as results that do. Results that do not support your hypothesis do not mean that your experiment has “failed” or that you should make up false results. So, for this section of the lab report, it is extremely important that you always represent the actual data you obtained in the experiment.

Analysis and Discussion

This section is the real meat of your lab report. Here you will present an analysis of the results you obtained in your experiment and whether they do or do not support your hypothesis. Note that this is the terminology that should be used when discussing your hypothesis in light of your results (not “prove” or “disprove”). Remember, results that do not support your hypothesis are not invalid, and this is your chance to explain why you think these unexpected results occurred.

This portion of your lab report is also an opportunity to discuss any shortcomings of the experiment, materials, or methods, and a place to provide suggestions for things that could be improved if the experiment was performed again. Additionally, you may suggest related investigations that could be performed given the results of your experiment (e.g., testing different brands of organic fertilizer on potato plant growth if a fertilizer you initially used did not work as well as you expected).

You should strive to clearly explain the meaning behind your results and any implications these results have on the information discussed in your introduction/background section. You should reference your results in any statements you make about your experiment, either by quoting data directly (e.g., “the plants grew an average of 4.5 cm taller”) or by referencing the figure, table, or graph number (e.g., “As shown in Table 1, organic fertilizer produced greater average plant growth than synthetic fertilizer”).

In some cases, your teacher may provide a list of questions that should be answered in this section. If this is the case, remember to reference this list and make sure all questions have been addressed in your text. These questions can also potentially serve as a useful way to organize your analysis and discussion.

Sometimes, a concluding sentence or two is written at the end of the previous section (Analysis and Discussion), and sometimes it is given its own section. Either way, you will summarize your big takeaways from the experiment (what you were testing and whether your results support your hypothesis or not). This is usually the section of your AP Biology lab report that makes you think a lot about the big picture of your experiment.

Works Cited

In this final section of your lab report, you will list all the sources you used to create your lab report. At the minimum, this should include your provided lab manual and textbook. If you used any other books or online sources, make sure to list them here as well. Your teacher will likely provide you with the preferred lab report format for this section, but if not, American Psychological Association Style (APA format) is what you should use.

This section is a good reminder that you can absolutely use outside reliable sources for inspiration and information, but your lab report should always be in your own words and should never contain any plagiarized material.

Now you have learned key tips on how to write an AP Biology lab report in the best manner possible. As you go through your AP Biology class, you will have plenty of opportunities to create AP Biology lab report examples in the format your teacher asks for. To maximize your learning experience, try taking some AP Biology practice questions in the unit you are covering in class. It will help you pair all the scientific reasoning you did in the lab with the content tested for that unit of the AP Biology exam!

Related Topics

We use cookies to learn how you use our website and to ensure that you have the best possible experience. By continuing to use our website, you are accepting the use of cookies. Learn More

AP® Biology

The chi square test: ap® biology crash course.

• The Albert Team
• Last Updated On: March 7, 2024

The statistics section of the AP® Biology exam is without a doubt one of the most notoriously difficult sections. Biology students are comfortable with memorizing and understanding content, which is why this topic seems like the most difficult to master. In this article,  The Chi Square Test: AP® Biology Crash Course , we will teach you a system for how to perform the Chi Square test every time. We will begin by reviewing some topics that you must know about statistics before you can complete the Chi Square test. Next, we will simplify the equation by defining each of the Chi Square variables. We will then use a simple example as practice to make sure that we have learned every part of the equation. Finally, we will finish with reviewing a more difficult question that you could see on your AP® Biology exam .

Null and Alternative Hypotheses

As background information, first you need to understand that a scientist must create the null and alternative hypotheses prior to performing their experiment. If the dependent variable is not influenced by the independent variable , the null hypothesis will be accepted. If the dependent variable is influenced by the independent variable, the data should lead the scientist to reject the null hypothesis . The null and alternative hypotheses can be a difficult topic to describe. Let’s look at an example.

Consider an experiment about flipping a coin. The null hypothesis would be that you would observe the coin landing on heads fifty percent of the time and the coin landing on tails fifty percent of the time. The null hypothesis predicts that you will not see a change in your data due to the independent variable.

The alternative hypothesis for this experiment would be that you would not observe the coins landing on heads and tails an even number of times. You could choose to hypothesize you would see more heads, that you would see more tails, or that you would just see a different ratio than 1:1. Any of these hypotheses would be acceptable as alternative hypotheses.

Defining the Variables

Now we will go over the Chi-Square equation. One of the most difficult parts of learning statistics is the long and confusing equations. In order to master the Chi Square test, we will begin by defining the variables.

This is the Chi Square test equation. You must know how to use this equation for the AP® Bio exam. However, you will not need to memorize the equation; it will be provided to you on the AP® Biology Equations and Formulas sheet that you will receive at the beginning of your examination.

Now that you have seen the equation, let’s define each of the variables so that you can begin to understand it!

•   X 2  :The first variable, which looks like an x, is called chi squared. You can think of chi like x in algebra because it will be the variable that you will solve for during your statistical test. •   ∑ : This symbol is called sigma. Sigma is the symbol that is used to mean “sum” in statistics. In this case, this means that we will be adding everything that comes after the sigma together. •   O : This variable will be the observed data that you record during your experiment. This could be any quantitative data that is collected, such as: height, weight, number of times something occurs, etc. An example of this would be the recorded number of times that you get heads or tails in a coin-flipping experiment. •   E : This variable will be the expected data that you will determine before running your experiment. This will always be the data that you would expect to see if your independent variable does not impact your dependent variable. For example, in the case of coin flips, this would be 50 heads and 50 tails.

The equation should begin to make more sense now that the variables are defined.

Working out the Coin Flip

We have talked about the coin flip example and, now that we know the equation, we will solve the problem. Let’s pretend that we performed the coin flip experiment and got the following data:

Now we put these numbers into the equation:

Heads (55-50) 2 /50= .5

Tails (45-50) 2 /50= .5

Lastly, we add them together.

c 2 = .5+.5=1

Now that we have c 2 we must figure out what that means for our experiment! To do that, we must review one more concept.

Degrees of Freedom and Critical Values

Degrees of freedom is a term that statisticians use to determine what values a scientist must get for the data to be significantly different from the expected values. That may sound confusing, so let’s try and simplify it. In order for a scientist to say that the observed data is different from the expected data, there is a numerical threshold the scientist must reach, which is based on the number of outcomes and a chosen critical value.

Let’s return to our coin flipping example. When we are flipping the coin, there are two outcomes: heads and tails. To get degrees of freedom, we take the number of outcomes and subtract one; therefore, in this experiment, the degree of freedom is one. We then take that information and look at a table to determine our chi-square value:

We will look at the column for one degree of freedom. Typically, scientists use a .05 critical value. A .05 critical value represents that there is a 95% chance that the difference between the data you expected to get and the data you observed is due to something other than chance. In this example, our value will be 3.84.

Coin Flip Results

In our coin flip experiment, Chi Square was 1. When we look at the table, we see that Chi Square must have been greater than 3.84 for us to say that the expected data was significantly different from the observed data. We did not reach that threshold. So, for this example, we will say that we failed to reject the null hypothesis.

The best way to get better at these statistical questions is to practice. Next, we will go through a question using the Chi Square Test that you could see on your AP® Bio exam.

AP® Biology Exam Question

This question was adapted from the 2013 AP® Biology exam.

In an investigation of fruit-fly behavior, a covered choice chamber is used to test whether the spatial distribution of flies is affected by the presence of a substance placed at one end of the chamber. To test the flies’ preference for glucose, 60 flies are introduced into the middle of the choice chamber at the insertion point. A ripe banana is placed at one end of the chamber, and an unripe banana is placed at the other end. The positions of flies are observed and recorded after 1 minute and after 10 minutes. Perform a Chi Square test on the data for the ten minute time point. Specify the null hypothesis and accept or reject it.

Okay, we will begin by identifying the null hypothesis . The null hypothesis would be that the flies would be evenly distributed across the three chambers (ripe, middle, and unripe).

Next, we will perform the Chi-Square test just like we did in the heads or tails experiment. Because there are three conditions, it may be helpful to use this set up to organize yourself:

Ok, so we have a Chi Square of 48.9. Our degrees of freedom are 3(ripe, middle, unripe)-1=2. Let’s look at that table above for a confidence variable of .05. You should get a value of 5.99. Our Chi Square value of 48.9 is much larger than 5.99 so in this case we are able to reject the null hypothesis. This means that the flies are not randomly assorting themselves, and the banana is influencing their behavior.

The Chi Square test is something that takes practice. Once you learn the system of solving these problems, you will be able to solve any Chi Square problem using the exact same method every time! In this article, we have reviewed the Chi Square test using two examples. If you are still interested in reviewing the bio-statistics that will be on your AP® Biology Exam, please check out our article The Dihybrid Cross Problem: AP® Biology Crash Course . Let us know how studying is going and if you have any questions!

Need help preparing for your AP® Biology exam?

Albert has hundreds of AP® Biology practice questions, free response, and full-length practice tests to try out.

Interested in a school license?​

Popular posts.

AP® Score Calculators

Simulate how different MCQ and FRQ scores translate into AP® scores

AP® Review Guides

The ultimate review guides for AP® subjects to help you plan and structure your prep.

Core Subject Review Guides

Review the most important topics in Physics and Algebra 1 .

SAT® Score Calculator

See how scores on each section impacts your overall SAT® score

ACT® Score Calculator

See how scores on each section impacts your overall ACT® score

Grammar Review Hub

Comprehensive review of grammar skills

AP® Posters

Download updated posters summarizing the main topics and structure for each AP® exam.

AP Biology Exam Tips

The following strategies for answering the free-response questions will help you on exam day.

• Before beginning to solve the free-response questions, it is a good idea to read through all the questions to determine which ones you feel most prepared to answer. You can then proceed to solve the questions in a sequence that will allow you to perform your best.
• Monitor your time appropriately on the free-response section. You want to ensure that you do not spend too much time on one question that you do not have enough time to at least attempt to answer all of them.
• Show all the steps you took to reach your solution on questions involving calculations. If you do work that you think is incorrect, simply put an "X" through it, instead of spending time erasing it completely.
• Many free-response questions are divided into parts such as a, b, c, and d, with each part calling for a different response. Credit for each part is awarded independently, so you should attempt to solve each part. For example, you may receive no credit for your answer to part a, but still receive full credit for part b, c, or d. If the answer to a later part of a question depends on the answer to an earlier part, you may still be able to receive full credit for the later part, even if that earlier answer is wrong.
• Organize your answers as clearly and neatly as possible. You might want to label your answers according to the sub-part, such as (a), (b), (c), etc. This will assist you in organizing your thoughts, as well as helping to ensure that you answer all the parts of the free-response question.
• You should include the proper units for each number where appropriate. If you keep track of units as you perform your calculations, it can help ensure that you express answers in terms of the proper units. Depending on the exam question, it is often possible to lose points if the units are wrong or are missing from the answer.
• You should not use the "scattershot" or “laundry list” approach: i.e., write as many equations or lists of terms as you can, hoping that the correct one will be among them so that you can get partial credit. For exams that ask for TWO or THREE examples or equations, only the first two or three examples will be scored.
• Be sure to clearly and correctly label all graphs and diagrams accordingly. Read the question carefully, as this could include a graph title, x and y axes labels including units, a best fit line, etc.

Pay close attention to the task verbs used in the free-response questions. Each one directs you to complete a specific type of response. Here are the task verbs you’ll see on the exam:

• Calculate: Perform mathematical steps to arrive at a final answer, including algebraic expressions, properly substituted numbers, and correct labeling of units and significant figures.
• Construct/Draw: Create a diagram, graph, representation, or model that illustrates or explains relationships or phenomena. Labels may or may not be required.
• Describe: Provide relevant characteristics of a specified topic.
• Determine: Decide or conclude after reasoning, observation, or applying mathematical routines (calculations).
• Evaluate: Judge or determine the significance or importance of information, or the quality or accuracy of a claim.
• Explain: Provide information about how or why a relationship, process, pattern, position, situation, or outcome occurs, using evidence and/or reasoning to support or qualfiy a claim. Explain “how” typically requires analyzing the relationship, process, pattern, position, situation, or outcome; whereas, explain “why” typically requires analysis of motivations or reasons for the relationship, process, pattern, position, situation, or outcome.
• Identify: Indicate or provide information about a specified topic, without elaboration or explanation.
• Justify: Provide evidence to support, qualify, or defend a claim, and/or provide reasoning to explain how that evidence supports or qualifies the claim.
• Make a claim: Make an assertion that is based on evidence or knowledge.
• Predict/Make a prediction: Predict the causes or effects of a change in, or disruption to, one or more components in a relationship, pattern, process, or system.
• Represent: Use appropriate graphs, symbols, words, illustrations, and/or tables of numerical values to describe biological concepts, characteristics, and/or relationships
• State (the null/alternative hypothesis): Indicate or provide a hypothesis to support or defend a claim about a scientifically testable question.
• Support a claim: Provide reasoning to explain how evidence supports or qualifies a claim.

• Top AP Biology Exam Strategies

April 8, 2024

The two sections of the AP Biology exam test similar content but with different question types. The following strategies will help you do well on both sections of the AP Biology exam.

AP Biology Section I: Multiple-Choice Questions

Strategy #1: do not skip over the scenarios and/or diagrams presented in the stem of the question. .

A stem that contains a description of a scenario and/or a diagram or graph will precede many of the multiple-choice questions. In a testing situation where time is limited, students are sometimes tempted to save time by skipping over the stem and proceeding directly to the question. Don’t do this! Often, taking just 30 seconds to read over the data or scenario presented will make it easier to answer the question or questions that follow it. The scenario presented in the stem of the question often will have important background information that will help you answer the question. If you are presented with a graph, note the variables shown on each axis and their units , and try to detect any patterns in the data. In data tables or charts, note the column headings and their units , and observe any trends or patterns in the data. 

Strategy #2: Do NOT be afraid of organisms or genes you may not have heard of before. 

There are so many great examples of organisms, genes, and ecosystems that apply to the content of the AP Biology course, and no teacher or textbook can mention all of them. Any example that is not explicitly included in the AP Biology Course and Exam Description will be described in enough detail in the question so that you will have enough background information to answer the question. Therefore, don’t worry if you see a question about the CYP6M2 gene in Anopheles gambiae and you’ve never heard of either before! The stem of the question will tell you what you need to know about that gene and organism (for example, that the CYP6M2 gene confers insecticide resistance to Anopheles mosquitoes), so all you need to do is apply your knowledge and skills to that background information to find the correct answer. 

Strategy #3: Do NOT be tempted by the “distractors.”

Incorrect answer choices are called distractors. As you read each question, cover the answer choices with a piece of paper or your hand. Before you reveal the answer choices, think of the characteristics that a good answer to the question at hand will contain. Then, reveal the answer choices and choose the answer that best fits the characteristics you know a good answer will have. It is often easier to focus your brain on finding the best answer rather than trying to eliminate each of the distractors. 

Strategy #4: DO pace yourself. 

You will have 90 minutes to answer 60 multiple-choice questions. If it is taking you more than two minutes to answer a question, move on to the next question and go back to that question later. Just make sure to skip the bubble in the answer sheet for each question you skip so that the following answers are filled in in the correct bubbles. 

Strategy #5: DO answer every question.

There is no guessing penalty on the AP Biology exam. If you leave a question blank, you are guaranteed to not earn points for that question, so answer every question, even if you have to guess. Never leave a question blank on the AP Biology exam! Reserve the last two or three minutes of the time allotted for Section I to check that you have answered all of the questions and have not left any questions blank. 

AP Biology Section II: Free-Response Questions

Strategy #1: do not leave any questions blank. .

Even if you think you don’t know how to answer the question, reread the question to see what terms in the question you do know something about. Then, use those terms as the basis for your answer, keeping in mind the task verbs in the question. As in Section I, if you leave a question blank, you are guaranteed to not earn points on that question, but if you write something, you may earn some points that could make the difference between a score of a 3, 4, or 5. Never give up—remember, you CAN do this!

Strategy #2: Do NOT make any contradictory statements. 

For example, if you state that the function of the mitochondria is to generate energy for the cell (a correct statement) but then later in your response state that the function of the mitochondria is also to perform photosynthesis (an incorrect statement), you have made two contradictory statements. Thus, you will not earn any points for either of those statements. 

Strategy #3: DO plan your approach to Section II.

Take the first 5–10 minutes allotted for Section II to “read and rank.” Read all six free-response questions, and then place the number 1 next to the question you think will be the easiest for you, the number 2 next to the next easiest question, and so on. You do not have to answer the questions in the order they appear in the test. Sometimes the easiest free-response questions are at the end of this section, and if you get hung up on a more challenging question that appears earlier, you may never get to the easier questions you are likely to earn points on. 

Strategy #4: DO read each question carefully.

Read each question carefully at least two times. Each time you read the question, circle or underline key words, especially any bolded words (which are the action or task verbs), any numbers, or any words like and or or (which indicate whether all or some of the items mentioned need to be addressed). 

Strategy #5: DO pace yourself. 

You will have 90 minutes to complete all six free-response questions. Some of the free-response questions will require less time; others will require more time. Here is a suggested time plan for Section II:

• First 5–10 minutes for “read and rank”
• 20 minutes for each of the two long free-response questions for a total of 40 minutes
• 5–10 minutes for each of the four short free-response questions for a total of 20–40 minutes

Strategy #6: DO write legibly. 

This may seem obvious, but if your answer is unclear or unreadable, the AP reader cannot award you points for it. Use a black ballpoint pen to write your answer. If you make a mistake, just cross it out with a single strikethrough—any more than that is unnecessary. If your handwriting is particularly difficult to read, consider writing on every other line in the test booklet. Don’t worry about running out of pages—the test booklet usually contains more blank pages than are typically needed, and the test proctor is required to give you extra pages if you do run out of paper in the test booklet. 

Strategy #7: DO label your graphs completely with units. 

If a question asks you to construct a graph, always make sure the axes are labeled clearly with the appropriate units. A unitless graph will not earn points. Use consistent scaling on your axes, and give your graph a title. 

Strategy #8: DO label the parts of your answer appropriately. 

This makes it easier for the reader who scores your exam to award you points. However, if you happen to answer part (a) of a question in the section you labeled (b), the reader will still award you points for it. 

Strategy #9: DO use complete sentences. 

As per the instructions for Section II, use complete sentences in your answers. You will not be awarded points for bulleted lists. If you use a drawing in your answer, make sure to also describe it in complete sentences. 

Strategy #10: DO ATP (Address the Prompt). 

Do not waste time writing an introductory paragraph, a thesis statement, or a concluding paragraph. Do not restate the question—the reader knows what the question is! While you need to be clear in your writing, you are not being evaluated on your ability to write a well-constructed essay, as you might be in an AP English course. You ARE being evaluated on your knowledge of biology. Make sure you understand the question prompt and what it is asking you to do. Then, reread your answer to make sure you addressed all of the task verbs in the question and did not make any contradictory statements. 

Strategy #11: DO pay attention to the task verbs!

Pay attention to these action verbs, which are typically bolded in the long and short free-response questions, as these words indicate what the question requires you to provide in your response. Some of the most frequently used task verbs are the following: 

• Predict —state what you think will happen if a change is made in a system or process
• Justify —give evidence to support your prediction
• Make a claim —make a statement based on the available data or evidence
• Support a claim —give evidence to defend a claim
• Describe —note the characteristics of something
• Explain —state “why” or “how” something happens (Note: This is more demanding than describing.)
• Identify —provide the information that is asked for (Note: This is less demanding than describing.)
• Calculate —perform the requested calculation, and ALWAYS show your work and your units!
• Construct —make a graph (show units!) or a diagram that illustrates data or a relationship
• Determine —make a conclusion based on evidence 
• State — give a null hypothesis or an alternative hypothesis that is supported by data/evidence
• Evaluate —assess the validity or accuracy of a claim or hypothesis

AP Biology Resources

• About the AP Biology Exam
• Top 5 Study Topics and Tips for the AP Biology Exam
• AP Biology Short Free-Response Questions
• AP Biology Long Free-Response Questions

AP Psychology Resources

• What’s Tested on the AP Psychology Exam?
• Top 5 Study Tips for the AP Psychology Exam
• AP Psychology Key Terms
• Top AP Psychology Exam Multiple-Choice Question Tips
• Top AP Psychology Exam Free Response Questions Tips
• AP Psychology Sample Free Response Question

AP English Language and Composition Resources

• What’s Tested on the AP English Language and Composition Exam?
• Top 5 Tips for the AP English Language and Composition Exam
• Top Reading Techniques for the AP English Language and Composition Exam
• How to Answer the AP English Language and Composition Essay Questions 
• AP English Language and Composition Exam Sample Essay Questions
• AP English Language and Composition Exam Multiple-Choice Questions

AP Human Geography Resources

• What’s Tested On the AP Human Geography Exam?
• AP Human Geography FAQs
• AP Human Geography Question Types and Strategies
• Top 5 Study Tips for the AP Human Geography Exam

FOLLOW ALONG ON SOCIAL

Choose Your Test

• Search Blogs By Category
• College Admissions
• AP and IB Exams
• GPA and Coursework

What's in an AP Biology Syllabus? Guide and Examples

Advanced Placement (AP)

A great syllabus is the backbone of any AP course, but it can be challenging to create one that fits all the requirements and is easy for students to follow. In this article, I'll give you the ingredients you need for a solid AP Biology syllabus, including all the concepts and curricular requirements of the course.

I'll also provide a sample syllabus so you can get an idea of what a syllabus for this class might look like (if you're a student) or how you might structure your version of AP Biology (if you're a teacher). Finally, the end of this article is devoted to a few quick tips for teachers and students on how to successfully teach and learn the material.

What Does the AP Biology Course Cover?

The curriculum framework of AP Biology was revamped in 2012 and is now organized around four Big Ideas , which are overarching themes that connect the concepts you’ll learn in the course. 

Within each Big Idea are several “Enduring Understandings” that students are expected to develop by taking the course. These are slightly narrower themes that  can be broken down even further into smaller parts that are aligned with specific facts about biological functions.

I’ll list the Big Ideas and their corresponding Enduring Understandings in this article, along with the labs that fall under each category. I won’t go into the smaller concepts within the Enduring Understandings so that this guide doesn’t get too long to digest. If you’re interested in a detailed rundown of the more minute concepts involved in AP Biology,  check out this page .

As students explore the Big Ideas, they are also expected to learn several key scientific practices, and the classwork must cover certain curricular requirements.   After I go through the Big Ideas, I’ll list the scientific practices students should develop and the curricular requirements that any AP Biology syllabus is expected to fulfill.

The Four Big Ideas of AP Biology 

Big idea #1: the process of evolution drives the diversity and unity of life..

• Enduring Understanding 1.1: Change in the genetic makeup of a population over time is evolution.
• EU 1.2: Organisms are linked by lines of descent from common ancestry.
• EU 1.3: Life continues to evolve within a changing environment.
• EU 1.4: The origin of living systems is explained by natural processes.

Labs for Big Idea 1:

• Artificial selection
• Mathematical modeling (Hardy-Weinberg)
• Comparing DNA Sequences to Understand Evolutionary Relationships

Big Idea #2: Biological systems utilize free energy and molecular building blocks to grow, to reproduce and to maintain dynamic homeostasis.

• EU 2.1: Growth, reproduction and maintenance of living systems require free energy and matter.
• EU 2.2: Growth, reproduction and dynamic homeostasis require that cells maintain internal environments that are different from their external environments.
• EU 2.3: Organisms use feedback mechanisms to regulate growth and reproduction, and to maintain dynamic homeostasis.
• EU 2.4: Growth and dynamic homeostasis of a biological system are influenced by changes in the system’s environment.
• EU 2.5: Many biological processes involved in growth, reproduction and dynamic homeostasis include temporal regulation and coordination.

Labs for Big Idea 2:

• Diffusion and Osmosis
• Photosynthesis
• Cellular Respiration  

Big Idea #3: Living systems store, receive, transmit and respond to information essential to life processes

• EU 3.1: Heritable information provides for the continuity of life.
• EU 3.2: Expression of genetic information involves cellular and molecular mechanisms.
• EU 3.3: The processing of genetic information is imperfect and is a source of genetic variation.
• EU 3.4: Cells communicate by generating, transmitting and receiving chemical signals.
• EU 3.5: Transmission of information results in changes within and between biological systems.

Labs for Big Idea 3:

• Cell Division: Mitosis and Meiosis
• Biotechnology: Bacterial Transformation
• Biotechnology: Restriction Enzyme Analysis of DNA  

Big Idea #4: Biological systems interact, and these systems and their interactions possess complex properties

• EU 4.1: Interactions within biological systems lead to complex properties.
• EU 4.2: Competition and cooperation are important aspects of biological systems.
• EU 4.3: Naturally occurring diversity among and between components within biological systems affects interactions with the environment.

Labs for Big Idea 4:

• Energy Dynamics
• Transpiration
• Fruit Fly Behavior
• Enzyme Activity  

Cooperation is always happening in biological systems! This is an approximation of what the inside of a cell looks like at any given time.

The Seven Scientific Practices of AP Biology 

#1:  The student can use representations and models to communicate scientific phenomena and solve scientific problems.

#2:   The student can use mathematics appropriately.

#3:  The student can engage in scientific questioning to extend thinking or to guide investigations within the context of the AP course.

#4: The student can plan and implement data collection strategies in relation to a particular scientific question. (Note: Data can be collected from many different sources, e.g., investigations, scientific observations, the findings of others, historic reconstruction and/or archived data.)

#5: The student can perform data analysis and evaluation of evidence.

#6: The student can work with scientific explanations and theories.

#7: The student is able to connect and relate knowledge across various scales, concepts and representations in and across domains.

The Curricular Requirements of AP Biology 

Here's a list of the requirements that an AP Biology course must fulfill to be considered an appropriate and thorough survey of the material:

• The course must use a college-level biology textbook published within the last ten years.
• Students must connect the Enduring Understandings of each Big Idea to at least one other Big Idea (for example, connect the evolutionary concepts in Big Idea 1 to the idea presented under Big Idea 3 that genetic information is sometimes processed imperfectly, and this leads to variation).
• Students should be assigned projects and activities outside of labs to meet the learning objectives for each Big Idea (for example, students might do an activity where they create a model of the cell cycle and give an oral presentation on its most important aspects).
• The course must give students the opportunity to connect biological knowledge to major social issues and current events (for example, a project researching stem cells and their potential to impact the medical field).
• Labs must give students the opportunity to apply the seven science practices I listed earlier, and the course has to go through at least two labs that correspond with each Big Idea.
• Labs must make up at least 25% of class time.
• Students should be asked to demonstrate verbal, written, and visual communication skills with lab reports, summaries of scientific literature or evidence, and oral presentations.

What Does an AP Biology Syllabus Look Like?

The College Board has released some sample syllabi to help guide teachers in their instruction of the new format of the AP Biology course.  The example that I’m looking at divides the class into nine different units of varying length. 

The resources for the course include:

• Reece, Jane, et al., Campbell Biology , 9th Edition, 2011, Pearson Benjamin Cummings
• www.campbellbiology.com  (The main text’s accompanying website that provides animations, investigations, PowerPoint and other audio-visual resources)
• Giffen, Cynthia and Heitz, Jean. Practicing Biology (to accompany Campbell- Reece Biology), 3rd Edition, 2008, Pearson Benjamin Cummings
• AP Biology Investigative Labs: an Inquiry Based Approach

I’ll give an overview of the topics discussed in each unit and the projects and labs students might complete throughout the year.   I’ll also provide the approximate length of each unit.  In this case, the class met four times a week for two 80-minute periods and two 50-minute periods (4 hours and 20 minutes a week total).

Sample AP Biology Syllabus

Unit 1: first week and introduction (4 classes).

Textbook Chapters:

• Introduction: Themes in the Study of Life
• The Chemical Context of Life
• Water and the Fitness of the Environment

Lecture and Discussion Topics:

• Darwin and the theory of natural selection
• Inquiry as a way to learn science
• Structure of atoms
• Emergent properties of water
• Make construction paper models of atoms and molecules to illustrate chemical concepts.
• Conduct an open inquiry on a biological topic of choice; formulate a question, design an experiment, and present the findings.

Unit 2: Biochemistry and Introduction to the Cell (11 classes)

4. Carbon and the Molecular Diversity of Life 5. The Structure and Function of Large Biological Molecules 6. A Tour of the Cell 7. Membrane Structure and Function

• The impact of carbon as the “backbone of life”
• How monomers build polymers, including the roles of nucleic acids
• Examples of organelles that are membrane bound to compartmentalize their functions
• Membrane structure and function
• Build a 3D cell membrane
• Diffusion and Osmosis Lab

Unit 3: Cellular Energy and Related Processes (14 classes)

8. An Introduction to Metabolism 9. Cellular Respiration 10. Photosynthesis

• Metabolic pathways
• Laws of energy transformation
• How ATP powers cellular work
• Enzyme structure and function
• Harvesting chemical energy: glycolysis, citric acid cycle, oxidative phosphorylation
• Light reactions and the Calvin cycle
• Evolution of alternative mechanism of carbon fixation
• Cellular Respiration Lab
• Photosynthesis Lab
• Enzyme Catalysis Lab

Unit 4: Cell Communication and the Cell Structure (9 classes)

11. Cell Communication 12. The Cell Cycle

• Evolution of cell signaling
• Reception, transduction, response
• How mitosis produces genetically identical daughter cells
• Evolution of mitosis
• How the eukaryotic cell cycle is regulated by a molecular control system
• Origin of cell communication

Projects and Labs:

• Pathways with Friends
• Modeling the Cell Cycle
• Cell Division and Mitosis Lab

Unit 5: Genetic Basis of Life (7 classes)

Textbook Chapters

13. Meiosis and Sexual Life Cycles 14. Mendel and the Gene Idea 15. The Chromosomal Basis of Inheritance

• Genes are passed from parents to offspring by the inheritance of chromosomes
• How meiosis reduces the number of chromosomes (diploid to haploid)
• Evolutionary significance of genetic variation that results from sexual life cycles
• Concepts of Mendelian genetics (laws of probability, inheritance patterns)
• Genes are located along chromosomes (concepts of gene linkage, mapping distance between genes, causes of genetic disorders)

Projects and Labs

• Fruit Fly Genetics Lab
• Meiosis Lab

Unit 6: Gene Activity and Biotechnology (13 classes)

16. The Molecular Basis of Inheritance 17. From Gene to Protein 18. Regulation of Gene Expression 19. Viruses  20. Biotechnology  21. Genomes and their Evolution

• DNA is the genetic material (historical experiments, DNA structure and function, DNA replication)
• Flow of genetic information (genetic code, role of other polymers, transcription, translation)
• Gene expression (operon systems in prokaryotes, eukaryotic gene expression)
• Virus structure and activity
• Restriction enzymes, plasmids, transformation
• DNA technology (how gel electrophoresis works and applications of this technology)
• DNA and Histone Model
• Biotechnology Lab 1: Transformation
• Gel Electrophoresis Lab

Unit 7: Evolution and Phylogeny (19 classes)

22. Descent with Modification: A Darwinian View of Life 23. The Evolution of Populations 24. The Origin of Species 25. The History of Life on Earth 26. Phylogeny and the Tree of Life 27. Bacteria and Archae

• How natural selection serves as a mechanism for evolution
• Scientific evidence supporting evolution
• Hardy-Weinberg concept
• How allele frequencies can be altered in a population
• Concepts of speciation
• Origin of life; fossil records
• Events in the “history of life” (origin of single-celled and multicellular organisms; mass extinctions; adaptive radiations)
• Comparing DNA Sequences Lab
• PBS Video: “What Darwin Never Knew”
• Evolutionary Time: The Geologic Time String
• Hardy-Weinberg  Problems

Unit 8: Diversity in the Biological World: Organism Form and Function (22 classes)

40. Basic Principles of Animal Form and Function 43. The Immune System 48. Neurons, Synapses, and Signaling 49. The Vertebrate Brain (Chapters 28-49 will be utilized to provide students with resources for the enduring understandings in this unit)

• Evolutionary trends (endosymbiosis, adaptations that allowed plants to move from water to land, reproductive adaptations of angiosperms, environmental roles of fungi, animal body plans, progressively complex derived characters in animal groups)
• Unique features of the angiosperm life cycles
• Signal transduction pathways (plant and animal hormones)
• Photoperiodism in plants
• Feedback control loops in animals
• Thermoregulation in animals
• Energy allocation and use in animals
• Examples of functioning units in mammal systems (alveoli in lungs, villi of small intestines, nephrons in kidneys)
• Structure and function in immune systems
• Structure and function in nervous systems (neurons, resting potential, action potential, synapses)
• Structure and function of the human brain
• Construct a cladogram for a group of organisms with certain traits
• Jumpin’ the Gap (students pretend to be components of neural communication)
• Research project on stem cells and whether they should be used to treat brain and spinal cord injuries

Unit 9: Ecology (17 classes)

• Aspects of animal behavior
• Aspects of biomes
• Models describing population growth
• Regulation of population growth
• Community interactions
• Species diversity and composition
• Community biodiversity
• Energy flow and chemical cycling in ecosystems
• Primary productivity
• Energy transfer between trophic levels
• Human activities that threaten biodiversity
• Fruit Fly Behavior Lab
• Dissolved Oxygen and Primary Productivity Lab
• Design a model of a biome
• Improving species richness by adding phosphate to a pond - how would you determine how much to add to avoid eutrophication? Present your hypothesis.
• Investigate how the fungus Pilobolus succeeds as a decomposer? Study adaptiveness of spore dispersal methods

Teaching Tips

Writing a great syllabus is the first order of business, but as you probably know, most of teaching is in the execution. If you’re a teacher trying to provide the best experience for your AP Biology students, here are a few tips you might consider using in your lessons.

#1: Provide Brief Lecture Outlines

Give brief outlines to students before you start your lecture so that they’ll have a clearer picture of what you’re going to cover. I say brief outlines because you don’t want to give them notes that list everything they need to know about the lecture topic.  List the main points of the lecture (around 3-5 of them), and list a couple of important subtopics under each. Provide plenty of space between concepts for students to write notes. They  should have some incentive to pay attention in class.  This will create a better environment where students aren't confused or tuned out.  

#2: Break Up Your Lectures With Class Discussions

I remember dreading double-period lecture classes in high school, and I was better than most high school students at sitting quietly and forgoing social interaction.  You should try to engage the class in a discussion midway through your lecture to break up the monotony.   I’d recommend calling on people randomly so that kids will have an incentive to pay attention and more introverted students will get a chance to participate in the discussion.

#3: Be Accessible During Labs

Chances are, kids will have tons of questions during labs. Sometimes the procedure is a little confusing or the results are different from what was expected.  Make a point of walking around the room and checking in with each lab group to ensure that everyone stays on task and students have a chance to ask questions.  This can also prevent students from doing the lab incorrectly and wasting time - you’ll catch mistakes early!  

#4: Model Your Tests After the Real AP Test

My AP Biology teacher gave us tests throughout the year whose questions were very similar to real AP test questions.   These tests were super challenging (I don’t think I ever got a solid A on any of them), but I was very well-prepared for the AP test.  Nothing on the exam was more difficult than the questions I had encountered on in-class tests , so I felt pretty confident.  

Tips for Students

Here are a few additional tips directed towards students who want to do well in AP Biology.  

#1: Do the Readings on Time

There’s a lot to cover in this class, so it’s critical that you keep up with the readings in your textbook.  If you fall behind, it will be hard to catch up.   There also may be important things that your textbook covers that your teacher won’t mention in lectures.  Plus, you’ll be able to participate in class discussions and avoid failing any pop quizzes!

#2: Take Notes During Lectures

Don’t zone out when your teacher is talking!  I know it can be difficult, but taking effective notes is a great skill to have for college and beyond.  Your notes will also help you study for in-class tests and, eventually, the AP test. It’s easier to study your own notes because they’ll be written in a way that you understand.  

#3: Ask Questions

Don’t be afraid to speak up in class discussions and engage with the lecture topics.  If you feel like you don’t understand a concept, ask your teacher about it. B elieve me, it's better than finding yourself totally lost later! Also, if you have any doubts about lab procedures or how you should write your lab reports, consult with your teacher before going forward.

AP Biology covers a huge amount of information, so writing a syllabus that organizes everything effectively is super important. The four main Big Ideas encompass many smaller themes, each of which covers a variety of complex concepts.

The College Board also requires classes to introduce students to seven scientific practices and fulfill a litany of other curricular requirements. Hopefully, the sample syllabus in this article gave you a good idea of what the structure of an AP Biology class should look like and how you might choose to cover all of the material.  Guiding students through this intimidating maze of concepts can be pretty difficult!

To review, some teaching strategies I recommend are:

• Providing brief lecture outlines
• Breaking lectures into more manageable chunks
• Being available for questions during labs
• Using tests that mimic the structure and content of the AP test

For students, here are a few other pieces of advice that I would suggest following:

• Keep up with the readings 
• Take notes on lectures
• Ask lots of questions

What's Next?

Looking for some good AP Biology review books? Check out my guide to the best books for this year's version of the test.

I've also written a complete study guide for the AP Biology test that goes through all the concepts and has links to free online resources that you can use to review.

Finally, this article goes through an analysis of whether AP Biology is more or less difficult in comparison to other AP classes and tests. It might be helpful if you're not sure about taking the course or just want some insight into how much you'll need to study for the test!

Trending Now

How to Get Into Harvard and the Ivy League

How to Get a Perfect 4.0 GPA

How to Write an Amazing College Essay

What Exactly Are Colleges Looking For?

ACT vs. SAT: Which Test Should You Take?

When should you take the SAT or ACT?

Get Your Free

Find Your Target SAT Score

Free Complete Official SAT Practice Tests

How to Get a Perfect SAT Score, by an Expert Full Scorer

Score 800 on SAT Math

Score 800 on SAT Reading and Writing

How to Improve Your Low SAT Score

Score 600 on SAT Math

Score 600 on SAT Reading and Writing

Find Your Target ACT Score

Complete Official Free ACT Practice Tests

How to Get a Perfect ACT Score, by a 36 Full Scorer

Get a 36 on ACT English

Get a 36 on ACT Math

Get a 36 on ACT Reading

Get a 36 on ACT Science

How to Improve Your Low ACT Score

Get a 24 on ACT English

Get a 24 on ACT Math

Get a 24 on ACT Reading

Get a 24 on ACT Science

Stay Informed

Get the latest articles and test prep tips!

Samantha is a blog content writer for PrepScholar. Her goal is to help students adopt a less stressful view of standardized testing and other academic challenges through her articles. Samantha is also passionate about art and graduated with honors from Dartmouth College as a Studio Art major in 2014. In high school, she earned a 2400 on the SAT, 5's on all seven of her AP tests, and was named a National Merit Scholar.

Ask a Question Below

Have any questions about this article or other topics? Ask below and we'll reply!

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

Size: 272 KB

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.

Text prompt

• Instructive
• Professional

10 Examples of Public speaking

20 Examples of Gas lighting

The Biology Corner

Biology Teaching Resources

Scientific Method Scenarios

In this activity, students work in groups to develop an experiment that answers the assigned question.  Each group gets a different question which can be printed and cut into strips to give randomly.

Sample Questions:

Does the wavelength of light affect a plant’s growth? Does the size of a fish tank determine how large a fish will grow? Do wounds heal faster when they are covered by band-aids?

Students design the experiment, and must also identify the a control group and the independent and dependent variables in their experiment.   There is also an advanced version of  this activity for AP Biology that has more rigorous questions, and asks students to establish a null hypothesis.

Students do not actually conduct their experiments, due to equipment and time constraints. Optionally, the teacher may choose one to conduct as a class demonstration, like the question about whether aspirin will keep cut flowers fresh.

NGSS:  8 Practices of Science

Shannan Muskopf