hypothesis called an educated guess

What is a scientific hypothesis?

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

A girl looks at plants in a test tube for a science experiment. What's her scientific hypothesis?

Hypothesis basics

What makes a hypothesis testable.

Types of hypotheses
Hypothesis versus theory

Additional resources

Bibliography.

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

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

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

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

Here are some examples of hypothesis statements:

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

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

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

Types of scientific hypotheses

Elementary-age students study alternative energy using homemade windmills during public school science class.

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

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

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

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

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

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

Scientific theory vs. scientific hypothesis

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

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

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

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

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

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

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

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

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

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

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

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

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National Center for Biotechnology Information - PubMed Central - On the scope of scientific hypotheses
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scientific hypothesis , an idea that proposes a tentative explanation about a phenomenon or a narrow set of phenomena observed in the natural world. The two primary features of a scientific hypothesis are falsifiability and testability, which are reflected in an “If…then” statement summarizing the idea and in the ability to be supported or refuted through observation and experimentation. The notion of the scientific hypothesis as both falsifiable and testable was advanced in the mid-20th century by Austrian-born British philosopher Karl Popper .

The formulation and testing of a hypothesis is part of the scientific method , the approach scientists use when attempting to understand and test ideas about natural phenomena. The generation of a hypothesis frequently is described as a creative process and is based on existing scientific knowledge, intuition , or experience. Therefore, although scientific hypotheses commonly are described as educated guesses, they actually are more informed than a guess. In addition, scientists generally strive to develop simple hypotheses, since these are easier to test relative to hypotheses that involve many different variables and potential outcomes. Such complex hypotheses may be developed as scientific models ( see scientific modeling ).

Depending on the results of scientific evaluation, a hypothesis typically is either rejected as false or accepted as true. However, because a hypothesis inherently is falsifiable, even hypotheses supported by scientific evidence and accepted as true are susceptible to rejection later, when new evidence has become available. In some instances, rather than rejecting a hypothesis because it has been falsified by new evidence, scientists simply adapt the existing idea to accommodate the new information. In this sense a hypothesis is never incorrect but only incomplete.

The investigation of scientific hypotheses is an important component in the development of scientific theory . Hence, hypotheses differ fundamentally from theories; whereas the former is a specific tentative explanation and serves as the main tool by which scientists gather data, the latter is a broad general explanation that incorporates data from many different scientific investigations undertaken to explore hypotheses.

Countless hypotheses have been developed and tested throughout the history of science . Several examples include the idea that living organisms develop from nonliving matter, which formed the basis of spontaneous generation , a hypothesis that ultimately was disproved (first in 1668, with the experiments of Italian physician Francesco Redi , and later in 1859, with the experiments of French chemist and microbiologist Louis Pasteur ); the concept proposed in the late 19th century that microorganisms cause certain diseases (now known as germ theory ); and the notion that oceanic crust forms along submarine mountain zones and spreads laterally away from them ( seafloor spreading hypothesis ).

Home » What is a Hypothesis – Types, Examples and Writing Guide

What is a Hypothesis – Types, Examples and Writing Guide

Table of Contents

Definition:

Hypothesis is an educated guess or proposed explanation for a phenomenon, based on some initial observations or data. It is a tentative statement that can be tested and potentially proven or disproven through further investigation and experimentation.

Hypothesis is often used in scientific research to guide the design of experiments and the collection and analysis of data. It is an essential element of the scientific method, as it allows researchers to make predictions about the outcome of their experiments and to test those predictions to determine their accuracy.

Types of Hypothesis

Types of Hypothesis are as follows:

Research Hypothesis

A research hypothesis is a statement that predicts a relationship between variables. It is usually formulated as a specific statement that can be tested through research, and it is often used in scientific research to guide the design of experiments.

Null Hypothesis

The null hypothesis is a statement that assumes there is no significant difference or relationship between variables. It is often used as a starting point for testing the research hypothesis, and if the results of the study reject the null hypothesis, it suggests that there is a significant difference or relationship between variables.

Alternative Hypothesis

An alternative hypothesis is a statement that assumes there is a significant difference or relationship between variables. It is often used as an alternative to the null hypothesis and is tested against the null hypothesis to determine which statement is more accurate.

Directional Hypothesis

A directional hypothesis is a statement that predicts the direction of the relationship between variables. For example, a researcher might predict that increasing the amount of exercise will result in a decrease in body weight.

Non-directional Hypothesis

A non-directional hypothesis is a statement that predicts the relationship between variables but does not specify the direction. For example, a researcher might predict that there is a relationship between the amount of exercise and body weight, but they do not specify whether increasing or decreasing exercise will affect body weight.

Statistical Hypothesis

A statistical hypothesis is a statement that assumes a particular statistical model or distribution for the data. It is often used in statistical analysis to test the significance of a particular result.

Composite Hypothesis

A composite hypothesis is a statement that assumes more than one condition or outcome. It can be divided into several sub-hypotheses, each of which represents a different possible outcome.

Empirical Hypothesis

An empirical hypothesis is a statement that is based on observed phenomena or data. It is often used in scientific research to develop theories or models that explain the observed phenomena.

Simple Hypothesis

A simple hypothesis is a statement that assumes only one outcome or condition. It is often used in scientific research to test a single variable or factor.

Complex Hypothesis

A complex hypothesis is a statement that assumes multiple outcomes or conditions. It is often used in scientific research to test the effects of multiple variables or factors on a particular outcome.

Applications of Hypothesis

Hypotheses are used in various fields to guide research and make predictions about the outcomes of experiments or observations. Here are some examples of how hypotheses are applied in different fields:

Science : In scientific research, hypotheses are used to test the validity of theories and models that explain natural phenomena. For example, a hypothesis might be formulated to test the effects of a particular variable on a natural system, such as the effects of climate change on an ecosystem.
Medicine : In medical research, hypotheses are used to test the effectiveness of treatments and therapies for specific conditions. For example, a hypothesis might be formulated to test the effects of a new drug on a particular disease.
Psychology : In psychology, hypotheses are used to test theories and models of human behavior and cognition. For example, a hypothesis might be formulated to test the effects of a particular stimulus on the brain or behavior.
Sociology : In sociology, hypotheses are used to test theories and models of social phenomena, such as the effects of social structures or institutions on human behavior. For example, a hypothesis might be formulated to test the effects of income inequality on crime rates.
Business : In business research, hypotheses are used to test the validity of theories and models that explain business phenomena, such as consumer behavior or market trends. For example, a hypothesis might be formulated to test the effects of a new marketing campaign on consumer buying behavior.
Engineering : In engineering, hypotheses are used to test the effectiveness of new technologies or designs. For example, a hypothesis might be formulated to test the efficiency of a new solar panel design.

How to write a Hypothesis

Here are the steps to follow when writing a hypothesis:

Identify the Research Question

The first step is to identify the research question that you want to answer through your study. This question should be clear, specific, and focused. It should be something that can be investigated empirically and that has some relevance or significance in the field.

Conduct a Literature Review

Before writing your hypothesis, it’s essential to conduct a thorough literature review to understand what is already known about the topic. This will help you to identify the research gap and formulate a hypothesis that builds on existing knowledge.

Determine the Variables

The next step is to identify the variables involved in the research question. A variable is any characteristic or factor that can vary or change. There are two types of variables: independent and dependent. The independent variable is the one that is manipulated or changed by the researcher, while the dependent variable is the one that is measured or observed as a result of the independent variable.

Formulate the Hypothesis

Based on the research question and the variables involved, you can now formulate your hypothesis. A hypothesis should be a clear and concise statement that predicts the relationship between the variables. It should be testable through empirical research and based on existing theory or evidence.

Write the Null Hypothesis

The null hypothesis is the opposite of the alternative hypothesis, which is the hypothesis that you are testing. The null hypothesis states that there is no significant difference or relationship between the variables. It is important to write the null hypothesis because it allows you to compare your results with what would be expected by chance.

Refine the Hypothesis

After formulating the hypothesis, it’s important to refine it and make it more precise. This may involve clarifying the variables, specifying the direction of the relationship, or making the hypothesis more testable.

Examples of Hypothesis

Here are a few examples of hypotheses in different fields:

Psychology : “Increased exposure to violent video games leads to increased aggressive behavior in adolescents.”
Biology : “Higher levels of carbon dioxide in the atmosphere will lead to increased plant growth.”
Sociology : “Individuals who grow up in households with higher socioeconomic status will have higher levels of education and income as adults.”
Education : “Implementing a new teaching method will result in higher student achievement scores.”
Marketing : “Customers who receive a personalized email will be more likely to make a purchase than those who receive a generic email.”
Physics : “An increase in temperature will cause an increase in the volume of a gas, assuming all other variables remain constant.”
Medicine : “Consuming a diet high in saturated fats will increase the risk of developing heart disease.”

Purpose of Hypothesis

The purpose of a hypothesis is to provide a testable explanation for an observed phenomenon or a prediction of a future outcome based on existing knowledge or theories. A hypothesis is an essential part of the scientific method and helps to guide the research process by providing a clear focus for investigation. It enables scientists to design experiments or studies to gather evidence and data that can support or refute the proposed explanation or prediction.

The formulation of a hypothesis is based on existing knowledge, observations, and theories, and it should be specific, testable, and falsifiable. A specific hypothesis helps to define the research question, which is important in the research process as it guides the selection of an appropriate research design and methodology. Testability of the hypothesis means that it can be proven or disproven through empirical data collection and analysis. Falsifiability means that the hypothesis should be formulated in such a way that it can be proven wrong if it is incorrect.

In addition to guiding the research process, the testing of hypotheses can lead to new discoveries and advancements in scientific knowledge. When a hypothesis is supported by the data, it can be used to develop new theories or models to explain the observed phenomenon. When a hypothesis is not supported by the data, it can help to refine existing theories or prompt the development of new hypotheses to explain the phenomenon.

When to use Hypothesis

Here are some common situations in which hypotheses are used:

In scientific research , hypotheses are used to guide the design of experiments and to help researchers make predictions about the outcomes of those experiments.
In social science research , hypotheses are used to test theories about human behavior, social relationships, and other phenomena.
I n business , hypotheses can be used to guide decisions about marketing, product development, and other areas. For example, a hypothesis might be that a new product will sell well in a particular market, and this hypothesis can be tested through market research.

Characteristics of Hypothesis

Here are some common characteristics of a hypothesis:

Testable : A hypothesis must be able to be tested through observation or experimentation. This means that it must be possible to collect data that will either support or refute the hypothesis.
Falsifiable : A hypothesis must be able to be proven false if it is not supported by the data. If a hypothesis cannot be falsified, then it is not a scientific hypothesis.
Clear and concise : A hypothesis should be stated in a clear and concise manner so that it can be easily understood and tested.
Based on existing knowledge : A hypothesis should be based on existing knowledge and research in the field. It should not be based on personal beliefs or opinions.
Specific : A hypothesis should be specific in terms of the variables being tested and the predicted outcome. This will help to ensure that the research is focused and well-designed.
Tentative: A hypothesis is a tentative statement or assumption that requires further testing and evidence to be confirmed or refuted. It is not a final conclusion or assertion.
Relevant : A hypothesis should be relevant to the research question or problem being studied. It should address a gap in knowledge or provide a new perspective on the issue.

Advantages of Hypothesis

Hypotheses have several advantages in scientific research and experimentation:

Guides research: A hypothesis provides a clear and specific direction for research. It helps to focus the research question, select appropriate methods and variables, and interpret the results.
Predictive powe r: A hypothesis makes predictions about the outcome of research, which can be tested through experimentation. This allows researchers to evaluate the validity of the hypothesis and make new discoveries.
Facilitates communication: A hypothesis provides a common language and framework for scientists to communicate with one another about their research. This helps to facilitate the exchange of ideas and promotes collaboration.
Efficient use of resources: A hypothesis helps researchers to use their time, resources, and funding efficiently by directing them towards specific research questions and methods that are most likely to yield results.
Provides a basis for further research: A hypothesis that is supported by data provides a basis for further research and exploration. It can lead to new hypotheses, theories, and discoveries.
Increases objectivity: A hypothesis can help to increase objectivity in research by providing a clear and specific framework for testing and interpreting results. This can reduce bias and increase the reliability of research findings.

Limitations of Hypothesis

Some Limitations of the Hypothesis are as follows:

Limited to observable phenomena: Hypotheses are limited to observable phenomena and cannot account for unobservable or intangible factors. This means that some research questions may not be amenable to hypothesis testing.
May be inaccurate or incomplete: Hypotheses are based on existing knowledge and research, which may be incomplete or inaccurate. This can lead to flawed hypotheses and erroneous conclusions.
May be biased: Hypotheses may be biased by the researcher’s own beliefs, values, or assumptions. This can lead to selective interpretation of data and a lack of objectivity in research.
Cannot prove causation: A hypothesis can only show a correlation between variables, but it cannot prove causation. This requires further experimentation and analysis.
Limited to specific contexts: Hypotheses are limited to specific contexts and may not be generalizable to other situations or populations. This means that results may not be applicable in other contexts or may require further testing.
May be affected by chance : Hypotheses may be affected by chance or random variation, which can obscure or distort the true relationship between variables.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

Appendices – Writing Guide, Types and Examples

Scope of the Research – Writing Guide and...

Thesis Statement – Examples, Writing Guide

Research Results Section – Writing Guide and...

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Words have precise meanings in science. For example, "theory," "law," and "hypothesis" don't all mean the same thing. Outside of science, you might say something is "just a theory," meaning it's a supposition that may or may not be true. In science, however, a theory is an explanation that generally is accepted to be true. Here's a closer look at these important, commonly misused terms.

A hypothesis is an educated guess, based on observation. It's a prediction of cause and effect. Usually, a hypothesis can be supported or refuted through experimentation or more observation. A hypothesis can be disproven but not proven to be true.

Example: If you see no difference in the cleaning ability of various laundry detergents, you might hypothesize that cleaning effectiveness is not affected by which detergent you use. This hypothesis can be disproven if you observe a stain is removed by one detergent and not another. On the other hand, you cannot prove the hypothesis. Even if you never see a difference in the cleanliness of your clothes after trying 1,000 detergents, there might be one more you haven't tried that could be different.

Scientists often construct models to help explain complex concepts. These can be physical models like a model volcano or atom or conceptual models like predictive weather algorithms. A model doesn't contain all the details of the real deal, but it should include observations known to be valid.

Example: The Bohr model shows electrons orbiting the atomic nucleus, much the same way as the way planets revolve around the sun. In reality, the movement of electrons is complicated but the model makes it clear that protons and neutrons form a nucleus and electrons tend to move around outside the nucleus.

A scientific theory summarizes a hypothesis or group of hypotheses that have been supported with repeated testing. A theory is valid as long as there is no evidence to dispute it. Therefore, theories can be disproven. Basically, if evidence accumulates to support a hypothesis, then the hypothesis can become accepted as a good explanation of a phenomenon. One definition of a theory is to say that it's an accepted hypothesis.

Example: It is known that on June 30, 1908, in Tunguska, Siberia, there was an explosion equivalent to the detonation of about 15 million tons of TNT. Many hypotheses have been proposed for what caused the explosion. It was theorized that the explosion was caused by a natural extraterrestrial phenomenon , and was not caused by man. Is this theory a fact? No. The event is a recorded fact. Is this theory, generally accepted to be true, based on evidence to-date? Yes. Can this theory be shown to be false and be discarded? Yes.

A scientific law generalizes a body of observations. At the time it's made, no exceptions have been found to a law. Scientific laws explain things but they do not describe them. One way to tell a law and a theory apart is to ask if the description gives you the means to explain "why." The word "law" is used less and less in science, as many laws are only true under limited circumstances.

Example: Consider Newton's Law of Gravity . Newton could use this law to predict the behavior of a dropped object but he couldn't explain why it happened.

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what is an educated guess called in science

Unveiling What an Educated Guess is Called in Science

Table of Contents

A scientific hypothesis is a fundamental component of the scientific method. It is often referred to as an “educated guess” in science because it is based on prior knowledge and observation. However, a hypothesis is more than just a random prediction. It requires active observation, background research, and the ability to be supported or refuted through experimentation or observation.

When scientists encounter a phenomenon in the natural world, they seek to explain it through a hypothesis. A hypothesis is a tentative, testable explanation that serves as a starting point for scientific inquiry. It is formulated based on existing knowledge and observations, and it provides a framework for conducting experiments and making predictions.

Understanding the basics of a hypothesis is essential for anyone interested in scientific inquiry. It is through the formulation and testing of hypotheses that scientific knowledge progresses and discoveries are made. In this article, I will delve into the intricacies of what an educated guess is called in science, explore the types of scientific hypotheses, and discuss the process of developing and evaluating hypotheses.

Key Takeaways:

A scientific hypothesis is an educated guess that seeks to explain a phenomenon in the natural world.
Hypotheses are more than random predictions; they require active observation, background research, and the possibility of being tested through experimentation or observation.
In science, hypotheses are important building blocks in the scientific method and serve as starting points for scientific inquiry.
Hypotheses can be formulated in different ways, such as null hypotheses and alternative hypotheses.
The process of developing a hypothesis involves careful observation, background research, and logical reasoning.

Understanding the Basics of a Hypothesis

A scientific hypothesis is a fundamental concept in scientific inquiry that allows researchers to make predictions and test their ideas through experimentation or observation. It serves as an educated guess or prediction based on prior knowledge and observation, helping scientists to formulate and investigate questions about the natural world.

At its core, a hypothesis is an idea that can be supported or refuted through carefully designed experiments or observations. It is typically written in the form of an if-then statement, articulating the anticipated outcome based on the proposed relationship between variables. This structure provides a clear framework for testing and evaluating the hypothesis.

The Characteristics of a Hypothesis

Testability: A hypothesis must be testable, meaning that it can be put to the test through experimentation or observation. This allows researchers to collect data and analyze it objectively, determining whether the hypothesis is supported or refuted.
Falsifiability: A hypothesis should be falsifiable, meaning that there must be a way to prove it wrong. This is essential for scientific inquiry, as hypotheses that cannot be proven wrong are not considered scientifically valid.
Specificity: A hypothesis should be specific and focused on addressing a particular problem or question. It should clearly define the variables being investigated and the predicted outcome, allowing for precise testing and evaluation.

By adhering to these characteristics, scientists can ensure that their hypotheses are sound and capable of advancing scientific understanding. The process of developing a hypothesis involves careful observation, background research, logical reasoning, and an understanding of existing theories and knowledge in the field.

Types of Scientific Hypotheses

In scientific research, hypotheses play a crucial role in shaping investigations and guiding the discovery process. There are two main types of scientific hypotheses: the null hypothesis and the alternative hypothesis.

Null Hypothesis

The null hypothesis predicts that there is no relationship between the variables being tested or no difference between the experimental groups. In other words, it assumes that any observed differences or relationships are due to chance or random variation. The null hypothesis is typically denoted as H 0 and is often used as a default starting point in scientific research.

Alternative Hypothesis

In contrast, the alternative hypothesis predicts that there will be a difference between the experimental groups or a relationship between the variables being tested. It proposes an alternative explanation or outcome that differs from the null hypothesis. The alternative hypothesis is denoted as H 1 or H a and is generally the hypothesis that researchers are more interested in. It is the hypothesis that can potentially lead to new discoveries and insights.

Understanding the distinction between the null hypothesis and the alternative hypothesis is essential for researchers to design experiments effectively and interpret their results accurately. By formulating and testing hypotheses, scientists can advance our knowledge and understanding of the natural world.

The Process of Developing a Hypothesis

Developing a hypothesis is a crucial step in the scientific process. It involves the use of scientific conjecture, speculation, and inference to formulate an educated guess or prediction about the outcome of an experiment or observation. A hypothesis serves as a starting point for scientific inquiry, guiding researchers in their quest for knowledge and understanding.

When developing a hypothesis, scientists rely on their prior knowledge and observations to make an informed estimation or supposition. They carefully consider existing theories and research findings to formulate a hypothesis that is grounded in scientific assumptions. This process requires logical reasoning and critical thinking, as well as a deep understanding of the subject area being investigated.

Factors to consider when developing a hypothesis:

Background research: Conducting a thorough review of existing literature and research findings to gather information and insights.
Observation: Making careful observations of the phenomenon or problem being investigated, noting any patterns, trends, or anomalies.
Logical reasoning: Applying logical reasoning to connect prior knowledge and observations, leading to the formulation of a hypothesis.

A well-developed hypothesis should be specific, testable, and focused on addressing the problem or question being investigated. It should propose a cause-and-effect relationship between variables and make a clear prediction or expectation about the outcome. This prediction can then be tested through experimentation or observation, allowing scientists to evaluate the validity of their hypothesis and draw meaningful conclusions.

In summary, the process of developing a hypothesis involves scientific conjecture, speculation, inference, and estimation based on prior knowledge and observation. It is a crucial step in the scientific method, setting the stage for further investigation and discovery. By formulating well-developed hypotheses, scientists can advance our understanding of the natural world and make meaningful contributions to their respective fields.

Writing a Hypothesis Statement

When it comes to conducting scientific research, a well-crafted hypothesis statement is crucial. It serves as the foundation for the entire experiment, guiding the direction and purpose of the investigation. In this section, I will discuss the key steps and considerations involved in writing a hypothesis statement.

First and foremost, a hypothesis statement should clearly state the relationship between the variables being investigated and the predicted outcome. It provides a concise summary of what the researcher intends to test and what they expect to discover. To ensure clarity and effectiveness, it is important to use specific language that leaves no room for ambiguity. By clearly defining the variables and their expected relationship, the hypothesis statement sets the stage for a focused and targeted experiment.

One commonly used format for writing a hypothesis statement is the if-then statement. It lays out the possibility (if) and the expected outcome (then) in a simple and logical manner. This format helps to establish a cause-and-effect relationship, making it easier to design and conduct the experiment. For example, “If the amount of sunlight increases, then the plant growth will also increase.” This hypothesis statement clearly identifies the variables (amount of sunlight and plant growth) and the predicted relationship between them.

Considerations for Writing a Hypothesis Statement:

Clearly state the relationship between variables.
Use specific language to avoid ambiguity.
Follow the if-then format to establish a cause-and-effect relationship.
Ensure the hypothesis is testable and measurable.
Keep the statement concise and focused on the problem or question being investigated.

By following these guidelines, researchers can develop hypothesis statements that are clear, specific, and testable. A well-written hypothesis statement not only provides a roadmap for conducting the experiment but also contributes to the overall validity and reliability of the research findings.

Testing and Evaluating a Hypothesis

Once a hypothesis is formulated, it is crucial to test and evaluate it through experimentation or observation. This step is vital in the scientific method as it allows researchers to gather data and analyze the results to determine if the hypothesis is supported or refuted. The process of testing and evaluating a hypothesis involves several key steps:

Designing the experiment: Researchers must carefully plan and design the experiment to ensure it is structured in a way that can effectively test the hypothesis. This includes determining the variables to be measured, the experimental groups or conditions, and the methods of data collection.
Collecting data: During the experiment or observation, data is collected through measurements, observations, and recordings. This data is essential in evaluating the hypothesis and drawing conclusions based on empirical evidence.
Analyzing the data: Once the data is collected, it is analyzed to identify patterns, trends, and relationships. Statistical analysis may be applied to determine the significance of any observed differences or correlations.
Evaluating the hypothesis: The results of the data analysis are then used to evaluate the hypothesis. If the data supports the predicted outcome, the hypothesis is considered to be supported. If the data contradicts the predicted outcome, the hypothesis is refuted. It is important to note that a hypothesis can never be proved correct 100% of the time, as there may always be exceptions or unknown factors.

The process of testing and evaluating a hypothesis is a critical component of scientific research. It provides empirical evidence to support or refute a hypothesis, allowing researchers to draw conclusions and make informed decisions based on the results. By following this rigorous process, scientists can build upon existing knowledge and contribute to the advancement of their respective fields.

Evaluating a Hypothesis: The Importance of Peer Review

Peer review is a crucial aspect of evaluating a hypothesis in the scientific community. After conducting an experiment, researchers submit their findings to scientific journals for publication. The submitted manuscript undergoes a rigorous peer review process wherein it is evaluated by experts in the field. These experts assess the methodology, data analysis, and validity of the conclusions drawn from the study.

Peer review ensures the quality and integrity of scientific research by subjecting it to the scrutiny of other knowledgeable researchers. It helps to identify any potential flaws, biases, or errors in the study’s design or interpretation of results. Peer-reviewed publications are generally considered more reliable and trustworthy, as they have undergone this rigorous evaluation process.

In conclusion, testing and evaluating a hypothesis are vital steps in the scientific method. Through careful experimentation, data collection, analysis, and peer review, researchers can determine the validity of their hypotheses. This process allows for the advancement of scientific knowledge and the development of evidence-based conclusions.

Hypothesis in Business Context

In a business context, a hypothesis plays a vital role in guiding decision-making and problem-solving. It serves as a tentative solution to a specific problem statement or strategic goal. Unlike in scientific experiments where bias should be avoided, business hypotheses are intentionally designed to affect change and address challenges within the organization.

Business Experimentation and Problem Solving

Business experimentation involves formulating hypotheses based on observations and measurements related to strategic priorities and goals. These hypotheses are aimed at testing whether a proposed solution or strategy is appropriate and effective in achieving the desired outcome. By conducting experiments and gathering data, businesses can evaluate the potential impact of different approaches and make informed decisions.

Testing and Iteration

Similar to scientific hypotheses, business hypotheses require testing and evaluation. The data collected during business experiments provides insights into the effectiveness of the proposed solutions. Through careful analysis, businesses can identify trends, patterns, and relationships that help refine their hypotheses and optimize their strategies. This iterative process allows organizations to adapt and improve their approaches based on real-world observations and feedback.

Tentative Solutions to Business Challenges

Business hypotheses serve as the foundation for problem-solving within organizations. They provide a structured framework for testing innovative ideas, exploring new markets, optimizing processes, and driving growth. By formulating hypotheses, businesses can take calculated risks and make informed decisions to address complex challenges and seize opportunities in a rapidly evolving market.

Difference Between Scientific Hypothesis and Business Hypothesis

Scientific hypotheses and business hypotheses serve distinct purposes and follow different approaches. While both types of hypotheses involve making informed guesses, they have key differences in terms of their focus and application.

In scientific research, a hypothesis is formulated to answer questions and explore the natural world. It is based on careful observation, background research, and logical reasoning. A scientific hypothesis is often testable and falsifiable, allowing researchers to conduct experiments and gather data to support or refute the hypothesis. The goal of scientific hypotheses is to contribute to the broader understanding of natural phenomena and develop theories that can withstand rigorous testing.

On the other hand, business hypotheses are developed to solve specific problems within a business context. They are informed by observations and measurements related to strategic priorities and goals. Business hypotheses are aimed at identifying potential solutions and testing their effectiveness in achieving desired outcomes. Unlike scientific experiments where bias should be avoided, business experimentation may involve intentionally affecting a certain change to find a solution to a specific problem.

Key Differences Between Scientific and Business Hypotheses:

Focus: Scientific hypotheses focus on understanding natural phenomena and contributing to scientific knowledge, while business hypotheses focus on problem-solving in a business context.
Approach: Scientific hypotheses involve careful observation, experimentation, and evaluation, while business hypotheses are informed by observations and measurements related to strategic priorities and goals.
Testing: Scientific hypotheses are typically testable and falsifiable, allowing for experiments and data collection, while business hypotheses involve intentional experimentation and may not require the same level of objectivity.
Goals: Scientific hypotheses aim to contribute to scientific understanding and develop theories, while business hypotheses aim to solve specific problems and achieve desired outcomes within a business context.

In summary, while both scientific and business hypotheses involve making educated guesses, they serve different purposes and follow different approaches. Scientific hypotheses contribute to scientific knowledge, while business hypotheses aim to solve problems in a business context and achieve desired outcomes.

Steps in the Scientific Method

The scientific method is a systematic approach to problem-solving that is used by scientists to uncover and understand the natural world. It consists of several steps that guide researchers through the process of formulating and testing hypotheses. By following these steps, scientists can gather evidence, analyze data, and draw conclusions that contribute to our understanding of the world.

The first step in the scientific method is defining and stating the problem or question. This involves identifying the specific issue or phenomenon that the researcher wants to investigate. It is important to clearly define the problem and establish a clear research question to guide the entire scientific process.

The second step is conducting research to gather information about the problem or question. This involves reviewing existing literature, conducting experiments, and gathering data from reliable sources. By examining previous research and current knowledge, scientists can gain a deeper understanding of the topic and identify any gaps in our understanding.
Once the research is complete, scientists can formulate a hypothesis. A hypothesis is an educated guess or prediction about the outcome of the experiment or observation. It is based on prior knowledge and observations, and it should be specific, testable, and grounded in existing theories. The hypothesis guides the design and execution of the experiment.
Next, scientists conduct an experiment or make observations to test the hypothesis. This involves carefully controlling variables, collecting data, and measuring outcomes. The data collected during the experiment is then analyzed to determine if it supports or refutes the hypothesis.
The final step in the scientific method is drawing a conclusion. Based on the analysis of the data, scientists can evaluate the hypothesis and determine whether it is supported or refuted. The conclusion may also involve identifying any limitations or weaknesses in the study and suggesting further research or experimentation to expand our understanding.

The scientific method is a vital tool in the pursuit of knowledge. By following these steps, scientists can systematically investigate and explore the natural world, uncovering new discoveries and advancing our understanding of the universe.

The Importance of Data Collection and Analysis in the Scientific Method

Data collection and analysis play a vital role in the scientific method. When conducting an experiment or making observations, researchers gather data by carefully observing, measuring, and recording relevant information. This data serves as the foundation for drawing conclusions, evaluating hypotheses, and making evidence-based decisions. Data collection allows scientists to gather empirical evidence and explore patterns, trends, and relationships within the data.

Once the data is collected, it is essential to analyze it effectively. Data analysis involves organizing, interpreting, and drawing meaningful insights from the collected data. By using statistical techniques, researchers can identify patterns, correlations, and significant findings within the data. This analysis helps refine and validate hypotheses, ensuring that scientific conclusions are based on solid evidence.

Furthermore, data collection and analysis allow for transparency and reproducibility in scientific research. By providing detailed descriptions of the data collection process and analysis methods, researchers enable others to replicate their work and verify the accuracy of the results. This fosters the advancement of scientific knowledge and allows for the exploration of new avenues of research.

The Role of Technology in Data Collection and Analysis

Advancements in technology have greatly enhanced data collection methods in scientific research. Tools such as sensors, data loggers, and imaging devices enable researchers to collect data with a high level of precision and accuracy.
Data analysis software and algorithms have also revolutionized the way scientists analyze and interpret data. These tools provide powerful statistical capabilities, allowing for complex analysis and visualization of large datasets.
The integration of technology in data collection and analysis has not only improved the efficiency and accuracy of scientific research but has also opened up new possibilities for interdisciplinary collaborations and discoveries.

In summary, data collection and analysis are integral components of the scientific method. They enable researchers to gather empirical evidence, draw conclusions, and make evidence-based decisions. Through effective data collection and rigorous analysis, scientists can uncover patterns and relationships within the data, refine hypotheses, and contribute to the advancement of scientific knowledge.

In conclusion, the hypothesis is a fundamental component of the scientific method. It serves as an educated guess or prediction based on prior knowledge and observation. However, it is more than just a random guess. A hypothesis requires active observation, background research, and the ability to be tested and verified through experimentation or observation.

Similarly, in a business context, a hypothesis takes the form of a tentative solution to a specific problem. It is informed by observations and measurements and is aimed at finding effective solutions to achieve desired outcomes. Business hypotheses are focused on problem-solving within the business environment and are driven by strategic priorities and goals.

Whether in science or business, hypotheses undergo testing, evaluation, and analysis to draw conclusions and make informed decisions. The data collected and analyzed during the process plays a crucial role in evaluating the hypothesis and making evidence-based choices. By following the scientific method or utilizing business experimentation, hypotheses can contribute to new discoveries, insights, and solutions.

To learn more about the scientific method, hypothesis testing, and problem-solving techniques, visit Exquisitive Education, where you can explore comprehensive resources and courses on these subjects.

What is an educated guess called in science?

An educated guess in science is called a scientific hypothesis.

What is a scientific hypothesis?

A scientific hypothesis is a tentative, testable explanation for a phenomenon in the natural world.

What are the types of scientific hypotheses?

There are two types of scientific hypotheses: the null hypothesis and the alternative hypothesis.

How do you develop a hypothesis?

Developing a hypothesis requires careful observation, background research, and logical reasoning.

How do you write a hypothesis statement?

A hypothesis statement should clearly state the relationship between the variables being investigated and the predicted outcome.

How do you test and evaluate a hypothesis?

A hypothesis is tested through experimentation or observation, and the data collected is analyzed to determine if it supports or refutes the hypothesis.

What is a hypothesis in a business context?

In a business context, a hypothesis is a tentative solution to a specific problem or goal.

What is the difference between a scientific hypothesis and a business hypothesis?

Scientific hypotheses focus on exploring the natural world, while business hypotheses aim to solve specific problems within a business context.

What are the steps in the scientific method?

The steps in the scientific method include defining the problem or question, conducting research, formulating a hypothesis, conducting experiments, analyzing data, drawing conclusions, and sharing results.

Why is data collection and analysis important in the scientific method?

Data collection and analysis help in drawing conclusions, evaluating hypotheses, and making informed decisions based on evidence obtained.

What is the role of a hypothesis in science?

A hypothesis is an important element of the scientific method, serving as a tentative explanation or prediction based on prior knowledge and observation.

About The Author

Ethan Emerson

Ethan Emerson is a passionate author and dedicated advocate for the transformative power of education. With a background in teaching and a love for writing, Ethan brings a unique blend of expertise and creativity to his contributions on ExquisitiveEducation.com .His articles are a delightful mix of insightful knowledge and engaging storytelling, aiming to inspire and empower learners of all ages. Ethan's mission is to ignite the spark of curiosity and foster a love for learning in every reader.Ethan Emerson, is your companion in the realm of general education exploration. With a passion for knowledge, He delves into the intricate world of Education Expenses & Discounts , uncovering financial insights for your educational journey. From the vitality of Physical Education to the synergy of Education & Technology , Ethan's here to bridge the gap between traditional and innovative learning methods. Discover the art of crafting impressive Resume & Personal Documentation in Education , as well as insights into diverse Career Paths, Degrees & Educational Requirements . Join Ethan in navigating through a sea of Educational Courses & Classes , exploring the nuances of various Education Systems , and understanding the empowering realm of Special Education . With an eye on Teaching & Teachers , He offers a glimpse into the world of educators who shape minds. Let's unlock Studying Tips & Learning Methods that turn education into a delightful journey of growth with Exquisitive Education .

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What Is a Hypothesis and How Do I Write One?

General Education

Think about something strange and unexplainable in your life. Maybe you get a headache right before it rains, or maybe you think your favorite sports team wins when you wear a certain color. If you wanted to see whether these are just coincidences or scientific fact, you would form a hypothesis, then create an experiment to see whether that hypothesis is true or not.

But what is a hypothesis, anyway? If you’re not sure about what a hypothesis is--or how to test for one!--you’re in the right place. This article will teach you everything you need to know about hypotheses, including:

Defining the term “hypothesis”
Providing hypothesis examples
Giving you tips for how to write your own hypothesis

So let’s get started!

What Is a Hypothesis?

Merriam Webster defines a hypothesis as “an assumption or concession made for the sake of argument.” In other words, a hypothesis is an educated guess . Scientists make a reasonable assumption--or a hypothesis--then design an experiment to test whether it’s true or not. Keep in mind that in science, a hypothesis should be testable. You have to be able to design an experiment that tests your hypothesis in order for it to be valid.

As you could assume from that statement, it’s easy to make a bad hypothesis. But when you’re holding an experiment, it’s even more important that your guesses be good...after all, you’re spending time (and maybe money!) to figure out more about your observation. That’s why we refer to a hypothesis as an educated guess--good hypotheses are based on existing data and research to make them as sound as possible.

Hypotheses are one part of what’s called the scientific method . Every (good) experiment or study is based in the scientific method. The scientific method gives order and structure to experiments and ensures that interference from scientists or outside influences does not skew the results. It’s important that you understand the concepts of the scientific method before holding your own experiment. Though it may vary among scientists, the scientific method is generally made up of six steps (in order):

Observation
Asking questions
Forming a hypothesis
Analyze the data
Communicate your results

You’ll notice that the hypothesis comes pretty early on when conducting an experiment. That’s because experiments work best when they’re trying to answer one specific question. And you can’t conduct an experiment until you know what you’re trying to prove!

Independent and Dependent Variables

After doing your research, you’re ready for another important step in forming your hypothesis: identifying variables. Variables are basically any factor that could influence the outcome of your experiment . Variables have to be measurable and related to the topic being studied.

There are two types of variables: independent variables and dependent variables. I ndependent variables remain constant . For example, age is an independent variable; it will stay the same, and researchers can look at different ages to see if it has an effect on the dependent variable.

Speaking of dependent variables... dependent variables are subject to the influence of the independent variable , meaning that they are not constant. Let’s say you want to test whether a person’s age affects how much sleep they need. In that case, the independent variable is age (like we mentioned above), and the dependent variable is how much sleep a person gets.

Variables will be crucial in writing your hypothesis. You need to be able to identify which variable is which, as both the independent and dependent variables will be written into your hypothesis. For instance, in a study about exercise, the independent variable might be the speed at which the respondents walk for thirty minutes, and the dependent variable would be their heart rate. In your study and in your hypothesis, you’re trying to understand the relationship between the two variables.

Elements of a Good Hypothesis

The best hypotheses start by asking the right questions . For instance, if you’ve observed that the grass is greener when it rains twice a week, you could ask what kind of grass it is, what elevation it’s at, and if the grass across the street responds to rain in the same way. Any of these questions could become the backbone of experiments to test why the grass gets greener when it rains fairly frequently.

As you’re asking more questions about your first observation, make sure you’re also making more observations . If it doesn’t rain for two weeks and the grass still looks green, that’s an important observation that could influence your hypothesis. You'll continue observing all throughout your experiment, but until the hypothesis is finalized, every observation should be noted.

Finally, you should consult secondary research before writing your hypothesis . Secondary research is comprised of results found and published by other people. You can usually find this information online or at your library. Additionally, m ake sure the research you find is credible and related to your topic. If you’re studying the correlation between rain and grass growth, it would help you to research rain patterns over the past twenty years for your county, published by a local agricultural association. You should also research the types of grass common in your area, the type of grass in your lawn, and whether anyone else has conducted experiments about your hypothesis. Also be sure you’re checking the quality of your research . Research done by a middle school student about what minerals can be found in rainwater would be less useful than an article published by a local university.

Writing Your Hypothesis

Once you’ve considered all of the factors above, you’re ready to start writing your hypothesis. Hypotheses usually take a certain form when they’re written out in a research report.

When you boil down your hypothesis statement, you are writing down your best guess and not the question at hand . This means that your statement should be written as if it is fact already, even though you are simply testing it.

The reason for this is that, after you have completed your study, you'll either accept or reject your if-then or your null hypothesis. All hypothesis testing examples should be measurable and able to be confirmed or denied. You cannot confirm a question, only a statement!

In fact, you come up with hypothesis examples all the time! For instance, when you guess on the outcome of a basketball game, you don’t say, “Will the Miami Heat beat the Boston Celtics?” but instead, “I think the Miami Heat will beat the Boston Celtics.” You state it as if it is already true, even if it turns out you’re wrong. You do the same thing when writing your hypothesis.

Additionally, keep in mind that hypotheses can range from very specific to very broad. These hypotheses can be specific, but if your hypothesis testing examples involve a broad range of causes and effects, your hypothesis can also be broad.

The Two Types of Hypotheses

Now that you understand what goes into a hypothesis, it’s time to look more closely at the two most common types of hypothesis: the if-then hypothesis and the null hypothesis.

#1: If-Then Hypotheses

First of all, if-then hypotheses typically follow this formula:

If ____ happens, then ____ will happen.

The goal of this type of hypothesis is to test the causal relationship between the independent and dependent variable. It’s fairly simple, and each hypothesis can vary in how detailed it can be. We create if-then hypotheses all the time with our daily predictions. Here are some examples of hypotheses that use an if-then structure from daily life:

If I get enough sleep, I’ll be able to get more work done tomorrow.
If the bus is on time, I can make it to my friend’s birthday party.
If I study every night this week, I’ll get a better grade on my exam.

In each of these situations, you’re making a guess on how an independent variable (sleep, time, or studying) will affect a dependent variable (the amount of work you can do, making it to a party on time, or getting better grades).

You may still be asking, “What is an example of a hypothesis used in scientific research?” Take one of the hypothesis examples from a real-world study on whether using technology before bed affects children’s sleep patterns. The hypothesis read s:

“We hypothesized that increased hours of tablet- and phone-based screen time at bedtime would be inversely correlated with sleep quality and child attention.”

It might not look like it, but this is an if-then statement. The researchers basically said, “If children have more screen usage at bedtime, then their quality of sleep and attention will be worse.” The sleep quality and attention are the dependent variables and the screen usage is the independent variable. (Usually, the independent variable comes after the “if” and the dependent variable comes after the “then,” as it is the independent variable that affects the dependent variable.) This is an excellent example of how flexible hypothesis statements can be, as long as the general idea of “if-then” and the independent and dependent variables are present.

#2: Null Hypotheses

Your if-then hypothesis is not the only one needed to complete a successful experiment, however. You also need a null hypothesis to test it against. In its most basic form, the null hypothesis is the opposite of your if-then hypothesis . When you write your null hypothesis, you are writing a hypothesis that suggests that your guess is not true, and that the independent and dependent variables have no relationship .

One null hypothesis for the cell phone and sleep study from the last section might say:

“If children have more screen usage at bedtime, their quality of sleep and attention will not be worse.”

In this case, this is a null hypothesis because it’s asking the opposite of the original thesis!

Conversely, if your if-then hypothesis suggests that your two variables have no relationship, then your null hypothesis would suggest that there is one. So, pretend that there is a study that is asking the question, “Does the amount of followers on Instagram influence how long people spend on the app?” The independent variable is the amount of followers, and the dependent variable is the time spent. But if you, as the researcher, don’t think there is a relationship between the number of followers and time spent, you might write an if-then hypothesis that reads:

“If people have many followers on Instagram, they will not spend more time on the app than people who have less.”

In this case, the if-then suggests there isn’t a relationship between the variables. In that case, one of the null hypothesis examples might say:

“If people have many followers on Instagram, they will spend more time on the app than people who have less.”

You then test both the if-then and the null hypothesis to gauge if there is a relationship between the variables, and if so, how much of a relationship.

4 Tips to Write the Best Hypothesis

If you’re going to take the time to hold an experiment, whether in school or by yourself, you’re also going to want to take the time to make sure your hypothesis is a good one. The best hypotheses have four major elements in common: plausibility, defined concepts, observability, and general explanation.

#1: Plausibility

At first glance, this quality of a hypothesis might seem obvious. When your hypothesis is plausible, that means it’s possible given what we know about science and general common sense. However, improbable hypotheses are more common than you might think.

Imagine you’re studying weight gain and television watching habits. If you hypothesize that people who watch more than twenty hours of television a week will gain two hundred pounds or more over the course of a year, this might be improbable (though it’s potentially possible). Consequently, c ommon sense can tell us the results of the study before the study even begins.

Improbable hypotheses generally go against science, as well. Take this hypothesis example:

“If a person smokes one cigarette a day, then they will have lungs just as healthy as the average person’s.”

This hypothesis is obviously untrue, as studies have shown again and again that cigarettes negatively affect lung health. You must be careful that your hypotheses do not reflect your own personal opinion more than they do scientifically-supported findings. This plausibility points to the necessity of research before the hypothesis is written to make sure that your hypothesis has not already been disproven.

#2: Defined Concepts

The more advanced you are in your studies, the more likely that the terms you’re using in your hypothesis are specific to a limited set of knowledge. One of the hypothesis testing examples might include the readability of printed text in newspapers, where you might use words like “kerning” and “x-height.” Unless your readers have a background in graphic design, it’s likely that they won’t know what you mean by these terms. Thus, it’s important to either write what they mean in the hypothesis itself or in the report before the hypothesis.

Here’s what we mean. Which of the following sentences makes more sense to the common person?

If the kerning is greater than average, more words will be read per minute.

If the space between letters is greater than average, more words will be read per minute.

For people reading your report that are not experts in typography, simply adding a few more words will be helpful in clarifying exactly what the experiment is all about. It’s always a good idea to make your research and findings as accessible as possible.

Good hypotheses ensure that you can observe the results.

#3: Observability

In order to measure the truth or falsity of your hypothesis, you must be able to see your variables and the way they interact. For instance, if your hypothesis is that the flight patterns of satellites affect the strength of certain television signals, yet you don’t have a telescope to view the satellites or a television to monitor the signal strength, you cannot properly observe your hypothesis and thus cannot continue your study.

Some variables may seem easy to observe, but if you do not have a system of measurement in place, you cannot observe your hypothesis properly. Here’s an example: if you’re experimenting on the effect of healthy food on overall happiness, but you don’t have a way to monitor and measure what “overall happiness” means, your results will not reflect the truth. Monitoring how often someone smiles for a whole day is not reasonably observable, but having the participants state how happy they feel on a scale of one to ten is more observable.

In writing your hypothesis, always keep in mind how you'll execute the experiment.

#4: Generalizability

Perhaps you’d like to study what color your best friend wears the most often by observing and documenting the colors she wears each day of the week. This might be fun information for her and you to know, but beyond you two, there aren’t many people who could benefit from this experiment. When you start an experiment, you should note how generalizable your findings may be if they are confirmed. Generalizability is basically how common a particular phenomenon is to other people’s everyday life.

Let’s say you’re asking a question about the health benefits of eating an apple for one day only, you need to realize that the experiment may be too specific to be helpful. It does not help to explain a phenomenon that many people experience. If you find yourself with too specific of a hypothesis, go back to asking the big question: what is it that you want to know, and what do you think will happen between your two variables?

Hypothesis Testing Examples

We know it can be hard to write a good hypothesis unless you’ve seen some good hypothesis examples. We’ve included four hypothesis examples based on some made-up experiments. Use these as templates or launch pads for coming up with your own hypotheses.

Experiment #1: Students Studying Outside (Writing a Hypothesis)

You are a student at PrepScholar University. When you walk around campus, you notice that, when the temperature is above 60 degrees, more students study in the quad. You want to know when your fellow students are more likely to study outside. With this information, how do you make the best hypothesis possible?

You must remember to make additional observations and do secondary research before writing your hypothesis. In doing so, you notice that no one studies outside when it’s 75 degrees and raining, so this should be included in your experiment. Also, studies done on the topic beforehand suggested that students are more likely to study in temperatures less than 85 degrees. With this in mind, you feel confident that you can identify your variables and write your hypotheses:

If-then: “If the temperature in Fahrenheit is less than 60 degrees, significantly fewer students will study outside.”

Null: “If the temperature in Fahrenheit is less than 60 degrees, the same number of students will study outside as when it is more than 60 degrees.”

These hypotheses are plausible, as the temperatures are reasonably within the bounds of what is possible. The number of people in the quad is also easily observable. It is also not a phenomenon specific to only one person or at one time, but instead can explain a phenomenon for a broader group of people.

To complete this experiment, you pick the month of October to observe the quad. Every day (except on the days where it’s raining)from 3 to 4 PM, when most classes have released for the day, you observe how many people are on the quad. You measure how many people come and how many leave. You also write down the temperature on the hour.

After writing down all of your observations and putting them on a graph, you find that the most students study on the quad when it is 70 degrees outside, and that the number of students drops a lot once the temperature reaches 60 degrees or below. In this case, your research report would state that you accept or “failed to reject” your first hypothesis with your findings.

Experiment #2: The Cupcake Store (Forming a Simple Experiment)

Let’s say that you work at a bakery. You specialize in cupcakes, and you make only two colors of frosting: yellow and purple. You want to know what kind of customers are more likely to buy what kind of cupcake, so you set up an experiment. Your independent variable is the customer’s gender, and the dependent variable is the color of the frosting. What is an example of a hypothesis that might answer the question of this study?

Here’s what your hypotheses might look like:

If-then: “If customers’ gender is female, then they will buy more yellow cupcakes than purple cupcakes.”

Null: “If customers’ gender is female, then they will be just as likely to buy purple cupcakes as yellow cupcakes.”

This is a pretty simple experiment! It passes the test of plausibility (there could easily be a difference), defined concepts (there’s nothing complicated about cupcakes!), observability (both color and gender can be easily observed), and general explanation ( this would potentially help you make better business decisions ).

Experiment #3: Backyard Bird Feeders (Integrating Multiple Variables and Rejecting the If-Then Hypothesis)

While watching your backyard bird feeder, you realized that different birds come on the days when you change the types of seeds. You decide that you want to see more cardinals in your backyard, so you decide to see what type of food they like the best and set up an experiment.

However, one morning, you notice that, while some cardinals are present, blue jays are eating out of your backyard feeder filled with millet. You decide that, of all of the other birds, you would like to see the blue jays the least. This means you'll have more than one variable in your hypothesis. Your new hypotheses might look like this:

If-then: “If sunflower seeds are placed in the bird feeders, then more cardinals will come than blue jays. If millet is placed in the bird feeders, then more blue jays will come than cardinals.”

Null: “If either sunflower seeds or millet are placed in the bird, equal numbers of cardinals and blue jays will come.”

Through simple observation, you actually find that cardinals come as often as blue jays when sunflower seeds or millet is in the bird feeder. In this case, you would reject your “if-then” hypothesis and “fail to reject” your null hypothesis . You cannot accept your first hypothesis, because it’s clearly not true. Instead you found that there was actually no relation between your different variables. Consequently, you would need to run more experiments with different variables to see if the new variables impact the results.

Experiment #4: In-Class Survey (Including an Alternative Hypothesis)

You’re about to give a speech in one of your classes about the importance of paying attention. You want to take this opportunity to test a hypothesis you’ve had for a while:

If-then: If students sit in the first two rows of the classroom, then they will listen better than students who do not.

Null: If students sit in the first two rows of the classroom, then they will not listen better or worse than students who do not.

You give your speech and then ask your teacher if you can hand out a short survey to the class. On the survey, you’ve included questions about some of the topics you talked about. When you get back the results, you’re surprised to see that not only do the students in the first two rows not pay better attention, but they also scored worse than students in other parts of the classroom! Here, both your if-then and your null hypotheses are not representative of your findings. What do you do?

This is when you reject both your if-then and null hypotheses and instead create an alternative hypothesis . This type of hypothesis is used in the rare circumstance that neither of your hypotheses is able to capture your findings . Now you can use what you’ve learned to draft new hypotheses and test again!

Key Takeaways: Hypothesis Writing

The more comfortable you become with writing hypotheses, the better they will become. The structure of hypotheses is flexible and may need to be changed depending on what topic you are studying. The most important thing to remember is the purpose of your hypothesis and the difference between the if-then and the null . From there, in forming your hypothesis, you should constantly be asking questions, making observations, doing secondary research, and considering your variables. After you have written your hypothesis, be sure to edit it so that it is plausible, clearly defined, observable, and helpful in explaining a general phenomenon.

Writing a hypothesis is something that everyone, from elementary school children competing in a science fair to professional scientists in a lab, needs to know how to do. Hypotheses are vital in experiments and in properly executing the scientific method . When done correctly, hypotheses will set up your studies for success and help you to understand the world a little better, one experiment at a time.

What’s Next?

If you’re studying for the science portion of the ACT, there’s definitely a lot you need to know. We’ve got the tools to help, though! Start by checking out our ultimate study guide for the ACT Science subject test. Once you read through that, be sure to download our recommended ACT Science practice tests , since they’re one of the most foolproof ways to improve your score. (And don’t forget to check out our expert guide book , too.)

If you love science and want to major in a scientific field, you should start preparing in high school . Here are the science classes you should take to set yourself up for success.

If you’re trying to think of science experiments you can do for class (or for a science fair!), here’s a list of 37 awesome science experiments you can do at home

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And now you are ready to make an educated guess
Remember a hypothesis is an educated guess that predicts the outcome of
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Scientific Methodology

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Educated Guess

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What is a scientific hypothesis? | Live Science
While an "educated guess" suggests a random prediction based on a person's expertise, developing a hypothesis requires active observation and background research. Hypothesis basics. The basic...
Scientific hypothesis | Definition, Formulation, & Example ...
The generation of a hypothesis frequently is described as a creative process and is based on existing scientific knowledge, intuition, or experience. Therefore, although scientific hypotheses commonly are described as educated guesses, they actually are more informed than a guess. In addition, scientists generally strive to develop simple ...
Hypothesis - Wikipedia
A trial solution to a problem is commonly referred to as a hypothesis—or, often, as an "educated guess" [14] [2] —because it provides a suggested outcome based on the evidence. However, some scientists reject the term "educated guess" as incorrect.
What is a Hypothesis – Types, Examples and Writing Guide
Hypothesis is an educated guess or proposed explanation for a phenomenon, based on some initial observations or data. It is a tentative statement that can be tested and potentially proven or disproven through further investigation and experimentation.
Scientific Hypothesis, Model, Theory, and Law - ThoughtCo
A hypothesis is an educated guess, based on observation. It's a prediction of cause and effect. Usually, a hypothesis can be supported or refuted through experimentation or more observation. A hypothesis can be disproven but not proven to be true.
7 Examples of an Educated Guess - Simplicable
Hypothesis. A hypothesis is a proposed theory that is later tested with experimentation. For example, a scientist who develops a theory that intestinal microbiome plays a role in a particular disease based on their understanding of processes in the body.
Understanding What is an Educated Guess in Science
An educated guess in science, commonly referred to as a hypothesis, is a prediction or statement that can be tested through experiments and observations. It is based on careful observations, thorough research, and existing knowledge about the subject.
Unveiling What an Educated Guess is Called in Science
A scientific hypothesis is an educated guess that seeks to explain a phenomenon in the natural world. Hypotheses are more than random predictions; they require active observation, background research, and the possibility of being tested through experimentation or observation.
What Is a Hypothesis and How Do I Write One? · PrepScholar
Merriam Webster defines a hypothesis as “an assumption or concession made for the sake of argument.” In other words, a hypothesis is an educated guess. Scientists make a reasonable assumption--or a hypothesis--then design an experiment to test whether it’s true or not. Keep in mind that in science, a hypothesis should be testable.
The hypothesis: An educated guess - ScienceDirect
A re- searcherâ€™s prediction of how the vari- ables relate to each other is called the hypothesis. Formulating the hypothesis is a delib- erate and formal process. It marks the beginning of the â€œdesigningâ€ phase of research, and it gives direction to the investigation.

What is a scientific hypothesis?

Hypothesis basics

Additional resources

Types of scientific hypotheses

Scientific theory vs. scientific hypothesis

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What is a Hypothesis – Types, Examples and Writing Guide

Types of Hypothesis

Research Hypothesis

Null Hypothesis

Alternative Hypothesis

Directional Hypothesis

Non-directional Hypothesis

Statistical Hypothesis

Composite Hypothesis

Empirical Hypothesis

Simple Hypothesis

Complex Hypothesis

Applications of Hypothesis

How to write a Hypothesis

Identify the Research Question

Conduct a Literature Review

Determine the Variables

Formulate the Hypothesis

Write the Null Hypothesis

Refine the Hypothesis

Examples of Hypothesis

Purpose of Hypothesis

When to use Hypothesis

Characteristics of Hypothesis

Advantages of Hypothesis

Limitations of Hypothesis

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Muhammad Hassan

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Appendices – Writing Guide, Types and Examples

Scope of the Research – Writing Guide and...

Thesis Statement – Examples, Writing Guide

Research Results Section – Writing Guide and...

Research Problem – Examples, Types and Guide

Data Verification – Process, Types and Examples

Scientific Hypothesis, Model, Theory, and Law

Unveiling What an Educated Guess is Called in Science

Key Takeaways:

Understanding the Basics of a Hypothesis

The Characteristics of a Hypothesis

Types of Scientific Hypotheses

Null Hypothesis

Alternative Hypothesis

The Process of Developing a Hypothesis

Factors to consider when developing a hypothesis:

Writing a Hypothesis Statement

Considerations for Writing a Hypothesis Statement:

Testing and Evaluating a Hypothesis

Evaluating a Hypothesis: The Importance of Peer Review

Hypothesis in Business Context

Business Experimentation and Problem Solving

Testing and Iteration

Tentative Solutions to Business Challenges

Difference Between Scientific Hypothesis and Business Hypothesis

Key Differences Between Scientific and Business Hypotheses:

Steps in the Scientific Method

The Importance of Data Collection and Analysis in the Scientific Method

The Role of Technology in Data Collection and Analysis

What is an educated guess called in science?

What is a scientific hypothesis?

What are the types of scientific hypotheses?

How do you develop a hypothesis?

How do you write a hypothesis statement?

How do you test and evaluate a hypothesis?

What is a hypothesis in a business context?

What is the difference between a scientific hypothesis and a business hypothesis?

What are the steps in the scientific method?

Why is data collection and analysis important in the scientific method?

What is the role of a hypothesis in science?

About The Author

Ethan Emerson

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