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Scientific Method Vocabulary Terms

The scientific method involves a hypothesis, variables, controls, experiments, and other concepts and terms that may be confusing. This is a glossary of key scientific method vocabulary terms and their definitions .

Glossary of Scientific Method Words

Anomaly: An anomaly is an observation that differs from expectation or from accepted scientific views. Anomalies lead scientists to revise a hypothesis or theory.

Central Limit Theorem:  The central limit theorem states that with a sufficiently large sample, the sample mean will be normally distributed. A normally distributed sample mean is necessary to apply the  t  test, so if you are planning to perform a statistical analysis of experimental data, it’s important to have a big sample.

Conclusion:  The conclusion is your determination of whether the hypothesis should be accepted or rejected. It is one of the steps of the scientific method.

Control Group :  The control group is the set of test subjects randomly assigned to  not  receive the experimental treatment. In other words, the independent variable is held constant for this group.

Control Variable :  A control is any variable that does not change during an experiment. It is also known as a  constant variable.

Correlation: A correlation is a relationship between two variables that can be used to predict the behavior or value of one variable if the other is known. Correlation is not the same as causality. In other words, correlating two variables doesn’t always imply one causes the other.

Data:  (singular: datum) Data refers to any facts, numbers, or values obtained in an experiment.

Data Table: This is a T-shaped diagram used to display data from a science experiment. It includes the values of the independent and dependent variables.

Dependent Variable:  The dependent variable is the variable that responds to the independent variable. It is the one that is measured in the experiment. It is also known as  the dependent measure ,  responding variable.

Double-blind :  When an experiment is double-blind, it means neither the researcher nor the subject knows whether the subject is receiving the treatment or a placebo. “Blinding” helps reduce biased results.

Empty Control Group:  An empty control group is a type of control group which does not receive any treatment, including a placebo.

Error : Error is a measure of the difference between a measured or calculated value and a true value.

Experiment : An experiment is a procedure that tests a hypothesis.

Experimental Group:  The experimental group is the set of test subjects randomly assigned to receive the experimental treatment.

Extraneous Variable:  Extraneous variables are extra variables (i.e., not the independent, dependent, or control variables) that may influence an experiment, but are not accounted for or measured or are beyond control. Examples may include factors you consider unimportant at the time of an experiment, such as the manufacturer of the glassware in a reaction or the color of paper used to make a paper airplane.

Fact: A fact is a statement based on evidence obtained from direct observation.

Graph: A graph is a picture that displays information. Examples of graphs include line graphs and bar graphs. The most common type of graph displays values of the independent and dependent variables.

Hypothesis:  A hypothesis is a prediction of whether the independent variable will have an effect on the dependent variable or a prediction of the nature of the effect.

Independence  or  Independently:  Independence means one factor does not exert influence on another. For example, what one study participant does should not influence what another participant does. They make decisions independently. Independence is critical for a meaningful statistical analysis.

Independent Random Assignment:  Independent random assignments means randomly selecting whether a test subject will be in a treatment or control group.

Independent Variable:  The independent variable is the variable that is manipulated or changed by the researcher. There is one independent variable in an experiment.

Independent Variable Levels: Independent variable levels refers to changing the independent variable from one value to another (e.g., different drug doses, different time duration). The different values are called “levels.”

Inferential Statistics:  Inferential statistics means applying statistics (math) to infer characteristics of a population based on a representative sample from the population.

Internal Validity:  An experiment is said to have internal validity if it can accurately determine whether the independent variable produces an effect.

Law : A scientific law is a generalization that describes what one expects to happen in a certain situation. For example, the law of gravity makes it possible to predict an object will fall if it is dropped. Laws can be used to predict behavior, but do not explain it.

Log Book: A log book or notebook records all of a scientist’s observations about an experiment. Entries are typically recorded in permanent ink.

Mean:  The mean is the average  calculated by adding up all the scores and then dividing by the number of scores.

Null Hypothesis :  Th null hypothesis is the “no difference” or “no effect” hypothesis, which predicts the treatment will not have an effect on the subject. The null hypothesis is easier to assess with a statistical analysis than other forms of a hypothesis.

Null Results (Nonsignificant Results):  If a researcher obtains nulls results, it means the results do not disprove the null hypothesis. Null results don’t  prove  the null hypothesis, because the results may have resulted from a lack of power. Some null results are type 2 errors.

Observation: An observation is information collected using one of the senses (sight, sound, touch, taste, scent).

p < 0.05:  This is an indication of how often chance alone could account for the effect of the experimental treatment. A value  p  < 0.05 means that 5 times out of a hundred, you could expect this difference between the two groups, purely by chance. Since the chance of the effect occurring by chance is so small, the researcher may conclude the experimental treatment did indeed have an effect. Note other  p  or probability values are possible. The 0.05 or 5% limit simply is a common benchmark of statistical significance.

Placebo (Placebo Treatment):  A placebo is a fake treatment that should have no effect, outside of the power of suggestion. Example: In drug trials, test patients may be given a pill containing the drug or a placebo, which resembles the drug (pill, injection, liquid) but doesn’t contain the active ingredient.

Placebo Effect : The placebo effect is a beneficial effect due to a subject’s belief in the power of the treatment. No active ingredient or other property of the placebo is responsible for the positive effect.

Population:  A population is the entire group the researcher is studying. If the researcher cannot gather data from the population, studying large random samples taken from the population may be used to estimate how the population would respond.

Power:  Power reflects the ability to observe differences or avoid making Type 2 errors .

Random   or Randomness:  To be random means to be selected or performed without following any pattern or method. To avoid unintentional bias, researchers often use random number generators or flip coins to make selections. (learn more)

Results:  The results are the explanation or interpretation of experimental data. This includes calculations made from the data.

Statistical Significance:  Statistical significance is the observation, based on the application of a statistical test, that a relationship probably is not due to pure chance. The probability is stated (e.g.,  p < 0.05) and the results are said to be  statistically significant .

Simple Experiment : A simple experiment is a basic experiment designed to assess whether there are a cause and effect relationship or test a prediction. A fundamental simple experiment may have only one test subject, compared with a controlled experiment, which has at least two groups.

Single-blind:  A single-blind conditions occurs when either the experimenter or subject is unaware whether the subject is getting the treatment or a placebo. Blinding the researcher helps prevent bias when the results are analyzed. Blinding the subject prevents the participant from having a biased reaction.

T-test:  The T-test is a common statistical data analysis applied to experimental data to test a hypothesis. The t-test computes the ratio between the difference between the group means and the standard error of the difference (a measure of the likelihood the group means could differ purely by chance). A rule of thumb is that the results are statistically significant if you observe a difference between the values that are three times larger than the standard error of the difference, but it’s best to look up the ratio required for significance on a  t  table.

Theory : A theory is a systematic explanation for phenomena, based on testing many hypotheses. Because they are evidence-based, theories are typically accepted by scientists, but they may be modified or discarded if new evidence is presented.

Type I Error (Type 1 error):  A type I error occurs when you reject the null hypothesis, but it was actually true. If you perform the t-test and set  p  < 0.05, there is less than a 5% chance you could make a Type I error by rejecting the hypothesis based on random fluctuations in the data.

Type II Error (Type 2 error):  A type II error occurs when you accept the null hypothesis, but it was actually false. The experimental conditions had an effect, but the researcher failed to find it statistically significant.

Further Study

Test your understanding of the scientific method glossary by taking a brief scientific method quiz . Solve a scientific method word search puzzle to gain familiarity with the terms.

Related Posts

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

Table of Contents

What Is Hypothesis?

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

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

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

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

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

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

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

Characteristics Of Hypothesis

A useful hypothesis must have the following qualities:

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

Sources Of Hypothesis

Sources of hypothesis are:

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

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

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

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

Types Of Hypothesis

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

Simple Hypothesis

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

Complex Hypothesis

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

Directional Hypothesis

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

Non-directional Hypothesis

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

Null Hypothesis

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

Associative and Causal Hypothesis

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

Examples Of Hypothesis

Examples of simple hypotheses:

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

Examples of a complex hypothesis:

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

Examples of Directional Hypothesis:

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

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

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

Examples of a null hypothesis:

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

Examples of Associative Hypothesis:

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

Functions Of Hypothesis

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

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

How will Hypothesis help in the Scientific Method?

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

Importance Of Hypothesis

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

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

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

Choose the best answer. 

Send Your Results (Optional)

Further Reading

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

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

Last updated on September 8th, 2023

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Biology library

Course: biology library   >   unit 1, the scientific method.

• Controlled experiments
• The scientific method and experimental design

Introduction

• Make an observation.
• Ask a question.
• Form a hypothesis , or testable explanation.
• Make a prediction based on the hypothesis.
• Test the prediction.
• Iterate: use the results to make new hypotheses or predictions.

Scientific method example: Failure to toast

1. make an observation..

• Observation: the toaster won't toast.

2. Ask a question.

• Question: Why won't my toaster toast?

3. Propose a hypothesis.

• Hypothesis: Maybe the outlet is broken.

4. Make predictions.

• Prediction: If I plug the toaster into a different outlet, then it will toast the bread.

5. Test the predictions.

• Test of prediction: Plug the toaster into a different outlet and try again.
• If the toaster does toast, then the hypothesis is supported—likely correct.
• If the toaster doesn't toast, then the hypothesis is not supported—likely wrong.

Logical possibility

Practical possibility, building a body of evidence, 6. iterate..

• Iteration time!
• If the hypothesis was supported, we might do additional tests to confirm it, or revise it to be more specific. For instance, we might investigate why the outlet is broken.
• If the hypothesis was not supported, we would come up with a new hypothesis. For instance, the next hypothesis might be that there's a broken wire in the toaster.

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Scientific Method Vocabulary Terms

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• Ph.D., Biomedical Sciences, University of Tennessee at Knoxville
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Scientific experiments involve variables , controls, hypotheses , and a host of other concepts and terms that might be confusing.

Glossary of Science Terms

Here is a glossary of important science experiment terms and definitions:

• Central Limit Theorem: States that with a large enough sample, the sample mean will be normally distributed. A normally distributed sample mean is necessary to apply the t- test, so if you are planning to perform a statistical analysis of experimental data, it's important to have a sufficiently large sample.
• Conclusion: Determination of whether the hypothesis should be accepted or rejected.
• Control Group: Test subjects randomly assigned to not receive the experimental treatment.
• Control Variable: Any variable that does not change during an experiment. Also known as a constant variable.
• Data   (singular: datum) : Facts, numbers, or values obtained in an experiment.
• Dependent Variable: The variable that responds to the independent variable. The dependent variable is the one being measured in the experiment. Also known as the dependent measure or responding variable.
• Double-Blind : When neither the researcher nor the subject knows whether the subject is receiving the treatment or a placebo. "Blinding" helps reduce biased results.
• Empty Control Group: A type of control group that does not receive any treatment, including a placebo.
• Experimental Group: Test subjects randomly assigned to receive the experimental treatment.
• Extraneous Variable: Extra variables (not independent, dependent, or control variables) that might influence an experiment but are not accounted for or measured or are beyond control. Examples might include factors you consider unimportant at the time of an experiment, such as the manufacturer of the glassware in a reaction or the color of paper used to make a paper airplane.
• Hypothesis: A prediction of whether the independent variable will have an effect on the dependent variable or a prediction of the nature of the effect. 
• Independence  or  Independently:  When one factor does not exert influence on another. For example, what one study participant does should not influence what another participant does. They make decisions independently. Independence is critical for a meaningful statistical analysis.
• Independent Random Assignment: Randomly selecting whether a test subject will be in a treatment or control group.
• Independent Variable : The variable that is manipulated or changed by the researcher.
• Independent Variable Levels: Changing the independent variable from one value to another (e.g., different drug doses, different amounts of time). The different values are called "levels."
• Inferential Statistics: Statistics (math) applied to infer characteristics of a population-based on a representative sample from the population.
• Internal Validity: When an experiment can accurately determine whether the independent variable produces an effect.
• Mean: The average calculated by adding all the scores and then dividing by the number of scores.
• Null Hypothesis : The "no difference" or "no effect" hypothesis, which predicts the treatment will not have an effect on the subject. The null hypothesis is useful because it is easier to assess with a statistical analysis than other forms of a hypothesis.
• Null Results (Nonsignificant Results): Results that do not disprove the null hypothesis. Null results don't prove the null hypothesis because the results may have resulted from a lack of power. Some null results are type 2 errors.
• p < 0.05: An indication of how often chance alone could account for the effect of the experimental treatment. A value p < 0.05 means that five times out of a hundred, you could expect this difference between the two groups purely by chance. Since the possibility of the effect occurring by chance is so small, the researcher may conclude the experimental treatment did indeed have an effect. Other p, or probability, values are possible. The 0.05 or 5% limit simply is a common benchmark of statistical significance.
• Placebo (Placebo Treatment):  A fake treatment that should have no effect outside the power of suggestion. Example: In drug trials, test patients may be given a pill containing the drug or a placebo, which resembles the drug (pill, injection, liquid) but doesn't contain the active ingredient.
• Population: The entire group the researcher is studying. If the researcher cannot gather data from the population, studying large random samples taken from the population can be used to estimate how the population would respond.
• Power: The ability to observe differences or avoid making Type 2 errors.
• Random or Randomness : Selected or performed without following any pattern or method. To avoid unintentional bias, researchers often use random number generators or flip coins to make selections.
• Results: The explanation or interpretation of experimental data.
• Simple Experiment : A basic experiment designed to assess whether there is a cause and effect relationship or to test a prediction. A fundamental simple experiment might have only one test subject, compared with a controlled experiment , which has at least two groups.
• Single-Blind: When either the experimenter or subject is unaware whether the subject is getting the treatment or a placebo. Blinding the researcher helps prevent bias when the results are analyzed. Blinding the subject prevents the participant from having a biased reaction.
• Statistical Significance: Observation, based on the application of a statistical test, that a relationship probably is not due to pure chance. The probability is stated (e.g., p < 0.05) and the results are said to be statistically significant.
• T-Test: Common statistical data analysis applied to experimental data to test a hypothesis. The t -test computes the ratio between the difference between the group means and the standard error of the difference, a measure of the likelihood the group means could differ purely by chance. A rule of thumb is that the results are statistically significant if you observe a difference between the values that is three times larger than the standard error of the difference, but it's best to look up the ratio required for significance on a t-table .
• Type I Error (Type 1 Error): Occurs when you reject the null hypothesis, but it was actually true. If you perform the t -test and set p < 0.05, there is less than a 5% chance you could make a Type I error by rejecting the hypothesis based on random fluctuations in the data.
• Type II Error (Type 2 Error): Occurs when you accept the null hypothesis, but it was actually false. The experimental conditions had an effect, but the researcher failed to find it statistically significant.
• What Is a Double Blind Experiment?
• The Difference Between Type I and Type II Errors in Hypothesis Testing
• Null Hypothesis Examples
• Example of a Permutation Test
• What Is a Hypothesis? (Science)
• Understanding Simple vs Controlled Experiments
• Six Steps of the Scientific Method
• What Is the Difference Between Alpha and P-Values?
• The Difference Between Control Group and Experimental Group
• Null Hypothesis Definition and Examples
• What Are the Elements of a Good Hypothesis?
• What Is a P-Value?
• What Is an Experiment? Definition and Design
• What Level of Alpha Determines Statistical Significance?
• What are Controlled Experiments?
• How To Design a Science Fair Experiment

Alphabetical

From the Greek word hypothesis meaning assumption or the basis of an argument, a hypothesis is a proposal intended to explain certain observations or phenomenon. In science, hypotheses represent the basis of scientific research , which is pursued to objectively determine whether or not a hypothesis is correct. Compare to theory .

Appears in modules:

• An Elegant Experiment to Test the Process of DNA Replication The work of Meselsohn and Stahl
• Atmospheric Chemistry Research that Changed Global Policy The work of Mario Molina
• Atomic Theory III Wave-particle duality and the electron
• Biodiversity I Definitions and patterns of diversity
• Carlos J. Finlay Eradicating yellow fever
• Cellular Organelles I Endosymbiosis and membrane-bound organelles
• Charles Darwin I The Origin of Species
• Creativity in Science How scientists decide what to study
• Data Analysis and Interpretation Revealing and explaining trends
• Description in Scientific Research Observations and multiple working hypotheses
• Discovery and Structure of Cells Cell theory, prokaryotes, and eukaryotes
• DNA I The genetic material
• DNA II The structure of DNA
• DNA III The replication of DNA
• Early Ideas about Matter From Democritus to Dalton
• Energy Metabolism I Glycolosis and the Krebs cycle
• Experimentation in Scientific Research Variables and controls in practice
• Factors that Control Earth's Temperature Energy from the sun and greenhouse gases
• From Stable Chromosomes to Jumping Genes The work of Barbara McClintock
• Gene Expression Enzymes and hereditary conditions
• History of Earth's Atmosphere I The origin of the modern atmosphere
• Independent Assortment Mendel's testcrosses and Punnett squares
• Inheritance Mendel's experiments and laws
• Introduction to Inferential Statistics Describing patterns and relationships in datasets
• Lipids Composition, structure, and function
• Luis Walter Alvarez Uncovering secrets of the atom and life on earth
• Membranes I Structure and function of biological membranes
• Modeling in Scientific Research Simplifying a system to make predictions
• Ocean Currents Mapping and explaining the ocean’s gyres
• Properties of Gases The gas laws and the ideal gas equation
• Revolutionzining Medicine with Monoclonal Antibodies The work of César Milstein
• Scientific Ethics Ethical standards and their implications
• Scientists and the Scientific Community The experiences that shape scientists
• Statistical Techniques Constructing a confidence interval
• The Carbon Cycle Geology, biology, and the impact of human activities
• The Mole and Atomic Mass Definitions, conversions, and Avogadro's number
• The Nature of Scientific Knowledge What is it and why should we trust it?
• The Phosphorus Cycle Phosphates and fertilizer
• The Piltdown Hoax A lesson on confirmation bias in science
• The Practice of Science An introduction to research methods
• The Process of Science Key concepts in thinking like a scientist
• Theories, Hypotheses, and Laws Definitions, examples, and their roles in science
• Thermodynamics I Caloric theory, latent heat, and the First Law of Thermodynamics
• Tracking Endangered Jaguars across the Border The work of Sergio Avila
• Waves and Wave Motion Describing waves

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Definition of hypothesis

Did you know.

The Difference Between Hypothesis and Theory

A hypothesis is an assumption, an idea that is proposed for the sake of argument so that it can be tested to see if it might be true.

In the scientific method, the hypothesis is constructed before any applicable research has been done, apart from a basic background review. You ask a question, read up on what has been studied before, and then form a hypothesis.

A hypothesis is usually tentative; it's an assumption or suggestion made strictly for the objective of being tested.

A theory , in contrast, is a principle that has been formed as an attempt to explain things that have already been substantiated by data. It is used in the names of a number of principles accepted in the scientific community, such as the Big Bang Theory . Because of the rigors of experimentation and control, it is understood to be more likely to be true than a hypothesis is.

In non-scientific use, however, hypothesis and theory are often used interchangeably to mean simply an idea, speculation, or hunch, with theory being the more common choice.

Since this casual use does away with the distinctions upheld by the scientific community, hypothesis and theory are prone to being wrongly interpreted even when they are encountered in scientific contexts—or at least, contexts that allude to scientific study without making the critical distinction that scientists employ when weighing hypotheses and theories.

The most common occurrence is when theory is interpreted—and sometimes even gleefully seized upon—to mean something having less truth value than other scientific principles. (The word law applies to principles so firmly established that they are almost never questioned, such as the law of gravity.)

This mistake is one of projection: since we use theory in general to mean something lightly speculated, then it's implied that scientists must be talking about the same level of uncertainty when they use theory to refer to their well-tested and reasoned principles.

The distinction has come to the forefront particularly on occasions when the content of science curricula in schools has been challenged—notably, when a school board in Georgia put stickers on textbooks stating that evolution was "a theory, not a fact, regarding the origin of living things." As Kenneth R. Miller, a cell biologist at Brown University, has said , a theory "doesn’t mean a hunch or a guess. A theory is a system of explanations that ties together a whole bunch of facts. It not only explains those facts, but predicts what you ought to find from other observations and experiments.”

While theories are never completely infallible, they form the basis of scientific reasoning because, as Miller said "to the best of our ability, we’ve tested them, and they’ve held up."

• proposition
• supposition

hypothesis , theory , law mean a formula derived by inference from scientific data that explains a principle operating in nature.

hypothesis implies insufficient evidence to provide more than a tentative explanation.

theory implies a greater range of evidence and greater likelihood of truth.

law implies a statement of order and relation in nature that has been found to be invariable under the same conditions.

Examples of hypothesis in a Sentence

These examples are programmatically compiled from various online sources to illustrate current usage of the word 'hypothesis.' Any opinions expressed in the examples do not represent those of Merriam-Webster or its editors. Send us feedback about these examples.

Word History

Greek, from hypotithenai to put under, suppose, from hypo- + tithenai to put — more at do

1641, in the meaning defined at sense 1a

Phrases Containing hypothesis

• counter - hypothesis
• nebular hypothesis
• null hypothesis
• planetesimal hypothesis
• Whorfian hypothesis

Articles Related to hypothesis

This is the Difference Between a...

This is the Difference Between a Hypothesis and a Theory

In scientific reasoning, they're two completely different things

Dictionary Entries Near hypothesis

hypothermia

hypothesize

Cite this Entry

“Hypothesis.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/hypothesis. Accessed 11 May. 2024.

Kids Definition

Kids definition of hypothesis, medical definition, medical definition of hypothesis, more from merriam-webster on hypothesis.

Nglish: Translation of hypothesis for Spanish Speakers

Britannica English: Translation of hypothesis for Arabic Speakers

Britannica.com: Encyclopedia article about hypothesis

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Science and the scientific method: Definitions and examples

Here's a look at the foundation of doing science — the scientific method.

The scientific method

Hypothesis, theory and law, a brief history of science, additional resources, bibliography.

Science is a systematic and logical approach to discovering how things in the universe work. It is also the body of knowledge accumulated through the discoveries about all the things in the universe. 

The word "science" is derived from the Latin word "scientia," which means knowledge based on demonstrable and reproducible data, according to the Merriam-Webster dictionary . True to this definition, science aims for measurable results through testing and analysis, a process known as the scientific method. Science is based on fact, not opinion or preferences. The process of science is designed to challenge ideas through research. One important aspect of the scientific process is that it focuses only on the natural world, according to the University of California, Berkeley . Anything that is considered supernatural, or beyond physical reality, does not fit into the definition of science.

When conducting research, scientists use the scientific method to collect measurable, empirical evidence in an experiment related to a hypothesis (often in the form of an if/then statement) that is designed to support or contradict a scientific theory .

"As a field biologist, my favorite part of the scientific method is being in the field collecting the data," Jaime Tanner, a professor of biology at Marlboro College, told Live Science. "But what really makes that fun is knowing that you are trying to answer an interesting question. So the first step in identifying questions and generating possible answers (hypotheses) is also very important and is a creative process. Then once you collect the data you analyze it to see if your hypothesis is supported or not."

The steps of the scientific method go something like this, according to Highline College :

• Make an observation or observations.
• Form a hypothesis — a tentative description of what's been observed, and make predictions based on that hypothesis.
• Test the hypothesis and predictions in an experiment that can be reproduced.
• Analyze the data and draw conclusions; accept or reject the hypothesis or modify the hypothesis if necessary.
• Reproduce the experiment until there are no discrepancies between observations and theory. "Replication of methods and results is my favorite step in the scientific method," Moshe Pritsker, a former post-doctoral researcher at Harvard Medical School and CEO of JoVE, told Live Science. "The reproducibility of published experiments is the foundation of science. No reproducibility — no science."

Some key underpinnings to the scientific method:

• The hypothesis must be testable and falsifiable, according to North Carolina State University . Falsifiable means that there must be a possible negative answer to the hypothesis.
• Research must involve deductive reasoning and inductive reasoning . Deductive reasoning is the process of using true premises to reach a logical true conclusion while inductive reasoning uses observations to infer an explanation for those observations.
• An experiment should include a dependent variable (which does not change) and an independent variable (which does change), according to the University of California, Santa Barbara .
• An experiment should include an experimental group and a control group. The control group is what the experimental group is compared against, according to Britannica .

The process of generating and testing a hypothesis forms the backbone of the scientific method. When an idea has been confirmed over many experiments, it can be called a scientific theory. While a theory provides an explanation for a phenomenon, a scientific law provides a description of a phenomenon, according to The University of Waikato . One example would be the law of conservation of energy, which is the first law of thermodynamics that says that energy can neither be created nor destroyed. 

A law describes an observed phenomenon, but it doesn't explain why the phenomenon exists or what causes it. "In science, laws are a starting place," said Peter Coppinger, an associate professor of biology and biomedical engineering at the Rose-Hulman Institute of Technology. "From there, scientists can then ask the questions, 'Why and how?'"

Laws are generally considered to be without exception, though some laws have been modified over time after further testing found discrepancies. For instance, Newton's laws of motion describe everything we've observed in the macroscopic world, but they break down at the subatomic level.

This does not mean theories are not meaningful. For a hypothesis to become a theory, scientists must conduct rigorous testing, typically across multiple disciplines by separate groups of scientists. Saying something is "just a theory" confuses the scientific definition of "theory" with the layperson's definition. To most people a theory is a hunch. In science, a theory is the framework for observations and facts, Tanner told Live Science.

The earliest evidence of science can be found as far back as records exist. Early tablets contain numerals and information about the solar system , which were derived by using careful observation, prediction and testing of those predictions. Science became decidedly more "scientific" over time, however.

1200s: Robert Grosseteste developed the framework for the proper methods of modern scientific experimentation, according to the Stanford Encyclopedia of Philosophy. His works included the principle that an inquiry must be based on measurable evidence that is confirmed through testing.

1400s: Leonardo da Vinci began his notebooks in pursuit of evidence that the human body is microcosmic. The artist, scientist and mathematician also gathered information about optics and hydrodynamics.

1500s: Nicolaus Copernicus advanced the understanding of the solar system with his discovery of heliocentrism. This is a model in which Earth and the other planets revolve around the sun, which is the center of the solar system.

1600s: Johannes Kepler built upon those observations with his laws of planetary motion. Galileo Galilei improved on a new invention, the telescope, and used it to study the sun and planets. The 1600s also saw advancements in the study of physics as Isaac Newton developed his laws of motion.

1700s: Benjamin Franklin discovered that lightning is electrical. He also contributed to the study of oceanography and meteorology. The understanding of chemistry also evolved during this century as Antoine Lavoisier, dubbed the father of modern chemistry , developed the law of conservation of mass.

1800s: Milestones included Alessandro Volta's discoveries regarding electrochemical series, which led to the invention of the battery. John Dalton also introduced atomic theory, which stated that all matter is composed of atoms that combine to form molecules. The basis of modern study of genetics advanced as Gregor Mendel unveiled his laws of inheritance. Later in the century, Wilhelm Conrad Röntgen discovered X-rays , while George Ohm's law provided the basis for understanding how to harness electrical charges.

1900s: The discoveries of Albert Einstein , who is best known for his theory of relativity, dominated the beginning of the 20th century. Einstein's theory of relativity is actually two separate theories. His special theory of relativity, which he outlined in a 1905 paper, " The Electrodynamics of Moving Bodies ," concluded that time must change according to the speed of a moving object relative to the frame of reference of an observer. His second theory of general relativity, which he published as " The Foundation of the General Theory of Relativity ," advanced the idea that matter causes space to curve.

In 1952, Jonas Salk developed the polio vaccine , which reduced the incidence of polio in the United States by nearly 90%, according to Britannica . The following year, James D. Watson and Francis Crick discovered the structure of DNA , which is a double helix formed by base pairs attached to a sugar-phosphate backbone, according to the National Human Genome Research Institute .

2000s: The 21st century saw the first draft of the human genome completed, leading to a greater understanding of DNA. This advanced the study of genetics, its role in human biology and its use as a predictor of diseases and other disorders, according to the National Human Genome Research Institute .

• This video from City University of New York delves into the basics of what defines science.
• Learn about what makes science science in this book excerpt from Washington State University .
• This resource from the University of Michigan — Flint explains how to design your own scientific study.

Merriam-Webster Dictionary, Scientia. 2022. https://www.merriam-webster.com/dictionary/scientia

University of California, Berkeley, "Understanding Science: An Overview." 2022. ​​ https://undsci.berkeley.edu/article/0_0_0/intro_01  

Highline College, "Scientific method." July 12, 2015. https://people.highline.edu/iglozman/classes/astronotes/scimeth.htm  

North Carolina State University, "Science Scripts." https://projects.ncsu.edu/project/bio183de/Black/science/science_scripts.html  

University of California, Santa Barbara. "What is an Independent variable?" October 31,2017. http://scienceline.ucsb.edu/getkey.php?key=6045  

Encyclopedia Britannica, "Control group." May 14, 2020. https://www.britannica.com/science/control-group  

The University of Waikato, "Scientific Hypothesis, Theories and Laws." https://sci.waikato.ac.nz/evolution/Theories.shtml  

Stanford Encyclopedia of Philosophy, Robert Grosseteste. May 3, 2019. https://plato.stanford.edu/entries/grosseteste/  

Encyclopedia Britannica, "Jonas Salk." October 21, 2021. https://www.britannica.com/ biography /Jonas-Salk

National Human Genome Research Institute, "​Phosphate Backbone." https://www.genome.gov/genetics-glossary/Phosphate-Backbone  

National Human Genome Research Institute, "What is the Human Genome Project?" https://www.genome.gov/human-genome-project/What  

‌ Live Science contributor Ashley Hamer updated this article on Jan. 16, 2022.

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[ hahy- poth - uh -sis , hi- ]

• a proposition, or set of propositions, set forth as an explanation for the occurrence of some specified group of phenomena, either asserted merely as a provisional conjecture to guide investigation working hypothesis or accepted as highly probable in the light of established facts.
• a proposition assumed as a premise in an argument.
• the antecedent of a conditional proposition.
• a mere assumption or guess.

/ haɪˈpɒθɪsɪs /

• a suggested explanation for a group of facts or phenomena, either accepted as a basis for further verification ( working hypothesis ) or accepted as likely to be true Compare theory
• an assumption used in an argument without its being endorsed; a supposition
• an unproved theory; a conjecture

/ hī-pŏth ′ ĭ-sĭs /

, Plural hypotheses hī-pŏth ′ ĭ-sēz′

• A statement that explains or makes generalizations about a set of facts or principles, usually forming a basis for possible experiments to confirm its viability.
• plur. hypotheses (heye- poth -uh-seez) In science, a statement of a possible explanation for some natural phenomenon. A hypothesis is tested by drawing conclusions from it; if observation and experimentation show a conclusion to be false, the hypothesis must be false. ( See scientific method and theory .)

Discover More

Derived forms.

• hyˈpothesist , noun

Other Words From

• hy·pothe·sist noun
• counter·hy·pothe·sis noun plural counterhypotheses
• subhy·pothe·sis noun plural subhypotheses

Word History and Origins

Origin of hypothesis 1

Synonym Study

Example sentences.

Each one is a set of questions we’re fascinated by and hypotheses we’re testing.

Mousa’s research hinges on the “contact hypothesis,” the idea that positive interactions among rival group members can reduce prejudices.

Do more research on it, come up with a hypothesis as to why it underperforms, and try to improve it.

Now is the time to test your hypotheses to figure out what’s changing in your customers’ worlds, and address these topics directly.

Whether computing power alone is enough to fuel continued machine learning breakthroughs is a source of debate, but it seems clear we’ll be able to test the hypothesis.

Though researchers have struggled to understand exactly what contributes to this gender difference, Dr. Rohan has one hypothesis.

The leading hypothesis for the ultimate source of the Ebola virus, and where it retreats in between outbreaks, lies in bats.

In 1996, John Paul II called the Big Bang theory “more than a hypothesis.”

To be clear: There have been no double-blind or controlled studies that conclusively confirm this hair-loss hypothesis.

The bacteria-driven-ritual hypothesis ignores the huge diversity of reasons that could push someone to perform a religious ritual.

And remember it is by our hypothesis the best possible form and arrangement of that lesson.

Taken in connection with what we know of the nebulæ, the proof of Laplace's nebular hypothesis may fairly be regarded as complete.

What has become of the letter from M. de St. Mars, said to have been discovered some years ago, confirming this last hypothesis?

To admit that there had really been any communication between the dead man and the living one is also an hypothesis.

"I consider it highly probable," asserted Aunt Maria, forgetting her Scandinavian hypothesis.

Related Words

• explanation
• interpretation
• proposition
• supposition

More About Hypothesis

What is a hypothesis .

In science, a hypothesis is a statement or proposition that attempts to explain phenomena or facts. Hypotheses are often tested to see if they are accurate.

Crafting a useful hypothesis is one of the early steps in the scientific method , which is central to every field of scientific experimentation. A useful scientific hypothesis is based on current, accepted scientific knowledge and is testable.

Outside of science, the word hypothesis is often used more loosely to mean a guess or prediction.

Why is hypothesis important?

The first records of the term hypothesis come from around 1590. It comes from the Greek term hypóthesis , meaning “basis, supposition.”

Trustworthy science involves experiments and tests. In order to have an experiment, you need to test something. In science, that something is called a hypothesis . It is important to remember that, in science, a verified hypothesis is not actually confirmed to be an absolute truth. Instead, it is accepted to be accurate according to modern knowledge. Science always allows for the possibility that new information could disprove a widely accepted hypothesis .

Related to this, scientists will usually only propose a new hypothesis when new information is discovered because there is no reason to test something that is already accepted as scientifically accurate.

Did you know … ?

It can take a long time and even the discovery of new technology to confirm that a hypothesis is accurate. Physicist Albert Einstein ’s 1916 theory of relativity contained hypotheses about space and time that have only been confirmed recently, thanks to modern technology!

What are real-life examples of hypothesis ?

While in science, hypothesis has a narrow meaning, in general use its meaning is broader.

"This study confirms the hypothesis that individuals who have been infected with COVID-19 have persistent objectively measurable cognitive deficits." (N=81,337) Ventilation subgroup show 7-point reduction in IQ https://t.co/50xrNNHC5E — Claire Lehmann (@clairlemon) July 23, 2021

Not everyone drives. They can walk, cycle, catch a train, tram etc. That’s alternatives. What’s your alternative in your hypothesis? — Barry (@Bazzaboy1982) July 27, 2021

What other words are related to hypothesis ?

• scientific method
• scientific theory

Quiz yourself!

True or False?

In science, a hypothesis must be based on current scientific information and be testable.

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Science Struck

Science – Glossary of Science Terms and Scientific Definitions

Science is a very vast subject that has innumerable words, terms, definitions, etc. The following article has a glossary list that will help you understand these difficult scientific terms and definitions at a glance.Just read on the following glossary to get a quick idea about some interesting terms.

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Many define science as an intellectual pursuit that involves the observation of natural occurrences and events, to discover the hidden facts and to formulate laws, theories and principles based on those facts.

A Glossary of Scientific Terms and Definitions

A to Z index

• Acceleration (a)

• Arithmetic Logic Unit (ALU)

B • Bacteriology The branch of science under microbiology that studies unicellular, microscopic organisms known as bacteria.  • Bandwidth It is the measurement calculated in bits per second, to know the amount of data that can be sent through a connection. • Biostasis A state in which the cell’s and tissue structure of an organism are preserved so that they can be restored again with the help of cell repair machines. • Bernoulli Effect Also known as Venturi effect, means that decrease in the pressure of fluid increases the velocity of the fluid. The Bernoulli’s principle and the equation of continuity form the basis of Bernoulli’s effect. • Biovorous An organism that can convert biological material into energy for sustenance is known as a biovorous organism.

• Bluetooth

• Carbohydrates

• Central Processing Unit (CPU) 

• Einstein Cosmological Constant (Lambda)

• Hertzsprung-Russell (HR) diagram The scatter graph of stars that explains the relationship between the absolute magnitudes of stars. The luminosity of the stars increases logarithmically up the vertical axis of the graph. Increase in temperature is plotted in increasing order from left to right on the horizontal axis.

• Hesperian Epoch Three broad time periods or epochs are used to explain the geologic history of the planet Mars. The oldest one being the Noachin, followed by Hesperian and Amazonian. The Hesperian Epochis known to extend from about 3.5 to 1.8 billion years ago.

• Heterochromatin The tightly packed DNA form which has limited transcription ability is known as heterochromatin.

• HiggsBoson The massive scalar elementary particle predicted and studied by the Standard Model in particle physics is known as the Higgs Boson.

• Highland Soil The sediments found on lunar highland surface, that are composed of broken rocks and mineral fragments is known as the highland soil.

• HTML HTML is a programming language that is used for designing static web pages. The collection of structuring and formatting tags that are used to create Web pages. HTML is the abbreviation for Hyper Text Markup Language. Know more on List of All HTML Tags .

• Hubble Constant

• Hubble Law The phenomenon that galaxies tend to move away from each other and the farther away they are, the faster they are separated is known as Hubble Law. The velocities of these galaxies increases proportionally to their distance. This phenomenon was discovered by US astronomer Edwin T. Hubble in 1929.

• Hubble Space Telescope The space telescope that was carried into orbit by space shuttle is called Hubble Space Telescope. It was taken into orbit in April 1990. Hubble telescope is used to observe the Universe in wavelength ranging from ultraviolet to infrared.

• Hyperpolarization The change in a cell’s membrane potential, due to the efflux of K + channels or the influx of Cl – through the Cl – channels, that makes it negative is known as hyperpolarization.

• Hypertext The mark-up language that leads to non-linear transfers of data is known as hypertext. World Wide Web is the most commonly used form of hypertext.

• Immortalizing Oncogene The growth of a primary cell that grows indefinitely in a culture due to transfer of a gene that is known as immortalizing oncogene.

• Independent Variable The variable among two related variables that can roam freely is known as independent variable. The other variable that is dependent on the former, is known as dependent variable.

• Indicator The substance that exhibits one color in acids and another color when added to an alkali is known as indicator. This helps to determine whether a liquid is an acid or a base/alkali.

• Induction When an object having magnetic or electrical properties produces similar properties in another object near it is known as induction.

• Inertia A bodies tendency to remain at rest or stay in motion unless it is acted upon by an external force is known as inertia.

• Infrared Light The light that has wavelength longer than that of visible light is called infrared. This light is measured from the nominal edge of visible red light at 0.74 micrometers (µ m), and can extend= conventionally to 300 µ m. This light is invisible to the human eye. It can be sensed as ‘heat’ or thermal radiation’.  Read more on Infrared Light Theraphy .

• Inositol Lipid

• Insulator A material through which electricity or heat cannot flow easily is known as an insulator

• Intensity Branching (%) It is the intensity of a radiation that is emitted during a radioactive decay. Know more on Meaning of radioactive Decay .

• Interferometer

• Karyokinesis

• Keratins The fibrous structural proteins that are tough and insoluble found in reptiles, birds, amphibians and mammals is known as keratin.

• Kelvin The fundamental unit of temperature that is not calibrated in terms of boiling point and freezing point of water but energy. 0 K is equal to the lowest temperature known as absolute zero. The freezing point of water on the Kelvin scale is -273 K and boiling point of water is 373 K.

• Kuiper Belt The spherical region of the outer solar system that has a population of ‘ice dwarfs’ is known as the Kuiper Belt. Know more on Facts About Dwarf Planets .

• Kinetic Energy

• Lagrangian Points

• Lambda Phage The virus particle that infects Eisherichia coli , is known as lambda phage. A lambda phage has a head, tail and tail fibers. The head of a lambda phage contains double-stranded DNA that is injected into the host bacteria for further replication to produce more phages.

• Leukocytes The white blood cells of the immune system, that defend the body against infectious diseases and foreign materials are known as leukocytes.

• Light The electromagnetic radiation that can be detected by the human eye is known as light.

• Lightning The powerful flash of electricity that is due to the negative electrical charges in clouds or between the cloud and ground is known as lightning. Know more on Different Types of Lightning .

• Light Year

• Mach Number

• Magnetism The force exerted by electric current on other electric currents is known as magnetism. Know more on History of Magnetism .

• Magnetic Field

• Media The substances through which the movement of light takes place like air, water, glass, etc. are known as media.

• Mathematics The branch of science that studies the quantity, structure, space and change is known as mathematics. It includes use of abstraction and logical reasoning. Know more on Math Terms – Glossary of Math Terms and Definitions .

• Meteor Shower

• Microbiology

• Microgravity

• Milky Way Our galaxy is observed as a misty band of light stretching across a night sky due to which it is known as milky way. There are one hundred million stars in our milky way. Know more on  Facts About The Milky Way .

• Nanosecond

• Nebula The cloud of dust and gas in space is known as nebula. Know more on Horsehead Nebula .

• Nerve The bundle of peripheral axons that provides a pathway for the passage of electrochemical nerve impulses transmitted along each of the axons is known as nerves. Know more on  Pheripheral Nervous System .

• Nervous System

• Neutron Star

• Nocturnal

• Nuclear Physics

  • Nuclein

• Occulation

• Okazaki Fragment The short DNA fragment with an RNA primer at the 5′ terminus that is created on the lagging strand during DNA replication is known as Okazaki fragment. • Oncogene A gene that is mutated or inappropriately expressed, that leads to cancer is known as oncogene. • Opposition The point where a planet that is far away from the Sun than the Earth, lines up with Sun and Earth is known as opposition. Opposition is the point when the planet is closest to Earth. •Optical Light The light that is detected by the human eye having a wavelength of 4000 and 7000 angstroms is known as optical light. Read more on Causes of Optical Illusions .

• Organelle

• Osmoregulation The osmotic pressure of the fluids inside an organism, that is actively regulated to maintain homeostasis of the organism’s water content is known as osmoregulation. It helps prevent the organisms fluids from becoming too dilute or too concentrated. • Ovulation The process of menstruation cycle in females, in which the mature ovarian follicle ruptures to discharge an ovum or egg to participate in reproduction is known as ovulation.

• Oxygenated Blood Blood that supplies oxygen bound to hemoglobin that is carried in red cells to the various tissues, and cells of the body is known as oxygenated blood. The heart pumps out the oxygenated blood through the important artery known as coronery artery. Read more on Anatomy of Coronary Artery .

P • Parasitism

• Particle A very small piece of an indivisible object is known as particle. Read more on  How Does the Collison Theory Work .  • Pedigree

• Period The time interval occurring between two consecutive and similar phases of a regularly occurring event is known as period. The rotation of Earth is the time taken to complete one revolution is an example of period.

• Peripheral The external devices like printers, disk drives, display monitors, keyboards, mouse, etc. that are attached to a computer are known as peripherals.

• Petrology The branch of science under geology that studies the origin, occurrence, formation, structure and composition of mineral assemblages and classification of rocks is known as petrology.

• Phobia The anxiety disorder exhibited by a person that is related to extreme and irrational fear of simple things or social situations is known as phobias. Know more on  List of All Phobias and Their Meanings . • Phosphatase

• Power (P)

Q • Quantum Theory

• Quantitative

• Radiation

• Ribonucleic Acid (RNA)

S • Satellite

• Scalar A quantity that can defined only by its magnitude like energy, temperature is known as scalar.

• Sea of Serenity The maria on the Moon’s nearside known as Mare Serenitatis. Know more on Facts about the Moon .

• Sea of Tranquility

• Southern Blotting The procedure in which DNA restriction fragments are transferred from agarose gel to a nitrocellulose filter, where the denatured DNA is hybridized to a radioactive probe. This process is also known as Southern Hybridization. • Static Electricity The electricity that is produced by friction is known as static electricity. Know more on  Static Electricity .

• Super Conductivity

T • Taq Polymerase

• TATA Box The sequence of adenine-thymine rich promoter located 25-30 bp upstream of a gene that is the binding site of RNA polymerase is known as TATA box.

• Template The synthesis of a complementary nucleotide strand on an RNA or single stranded DNA molecule is known as a template.

• Terminator Codon The three mRNA sequences (UGA,UAG,UAA) that do not code for an amino acid are known as terminator codons. These codons also known as ‘stop codon’ are a signal to the end of protein synthesis.

• Thermal Gradient The rate at which there is change in temperature with position is known as thermal gradient. Know more on Thermocouple . • Time

U • Ubiquitin

• Ultra Luminous Galaxies (ULIRG) The type of galaxy that appears too bright when observed at infrared wavelengths is known as ultra luminous galaxies.

• Ultraviolet Light The region of the electromagnetic spectrum ranging from 9.12 nm to 350 nm is known as ultraviolet light. UV rays are emitted from the Sun which are blocked by the Earth’s atmosphere. Know more on  Layer’s of Earth Atmosphere .

• Wavelength The distance between two peaks of a wave is known as wavelength. Know more on Electromagnetic Waves- Origin and Theory .

• Western Blot The process to detect specific proteins in a sample of tissue extract by gel electrophoresis is known as Western Blot.

• White Light The light that can be seen by the human eye that is made up of seven colors is known as white light. Know more on Color Spectrum Chart .

X • X- chromosome

• X- linked Disease

Radio Frequencies . • X- Ray

Y • Y-chromosome

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4.4: Glossary

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applied science: a form of science that solves real-world problems

atom: a basic unit of matter that cannot be broken down by normal chemical reactions

basic science: science that seeks to expand knowledge regardless of the short-term application of that knowledge

biology: the study of living organisms and their interactions with one another and their environments

biosphere: a collection of all ecosystems on Earth

cell: the smallest fundamental unit of structure and function in living things

community: a set of populations inhabiting a particular area

control: a part of an experiment that does not change during the experiment

deductive reasoning: a form of logical thinking that uses a general statement to forecast specific results

descriptive science: a form of science that aims to observe, explore, and find things out

ecosystem: all living things in a particular area together with the abiotic, nonliving parts of that environment

eukaryote: an organism with cells that have nuclei and membrane-bound organelles

evolution: the process of gradual change in a population that can also lead to new species arising from older species

falsifiable: able to be disproven by experimental results

homeostasis: the ability of an organism to maintain constant internal conditions

hypothesis-based science: a form of science that begins with a specific explanation that is then tested

hypothesis: a suggested explanation for an event, which can be testedinductive reasoninga form of logical thinking that uses related observations to arrive at a general conclusion

life science: a field of science, such as biology, that studies living things

macromolecule: a large molecule typically formed by the joining of smaller molecules

molecule: a chemical structure consisting of at least two atoms held together by a chemical bond

natural science: a field of science that studies the physical world, its phenomena, and processes

organ: a structure formed of tissues operating together to perform a common function

organ system: the higher level of organization that consists of functionally related organs

organelle: a membrane-bound compartment or sac within a cell

organism: an individual living entity

peer-reviewed article: a scientific report that is reviewed by a scientist’s colleagues before publication

phylogenetic tree: a diagram showing the evolutionary relationships among biological species based on similarities and differences in genetic or physical traits or both

physical science: a field of science, such as astronomy, physics, and chemistry, that studies nonliving matter

population: all individuals within a species living within a specific area

prokaryote: a unicellular organism that lacks a nucleus or any other membrane-bound organelle

science: knowledge that covers general truths or the operation of general laws, especially when acquired and tested by the scientific method

scientific law: a description, often in the form of a mathematical formula, for the behavior of some aspect of nature under certain specific conditions

scientific method: a method of research with defined steps that include experiments and careful observation

scientific theory: a thoroughly tested and confirmed explanation for observations or phenomena

tissue: a group of similar cells carrying out the same function

variable: a part of an experiment that can vary or change

Section Summary

Themes and concepts of biology.

Biology is the science of life. All living organisms share several key properties such as order, sensitivity or response to stimuli, reproduction, adaptation, growth and development, regulation, homeostasis, and energy processing. Living things are highly organized following a hierarchy that includes atoms, molecules, organelles, cells, tissues, organs, and organ systems. Organisms, in turn, are grouped as populations, communities, ecosystems, and the biosphere. Evolution is the source of the tremendous biological diversity on Earth today. A diagram called a phylogenetic tree can be used to show evolutionary relationships among organisms. Biology is very broad and includes many branches and sub disciplines. Examples include molecular biology, microbiology, neurobiology, zoology, and botany, among others.

The Process of Science

Biology is the science that studies living organisms and their interactions with one another and their environments. Science attempts to describe and understand the nature of the universe in whole or in part. Science has many fields; those fields related to the physical world and its phenomena are considered natural sciences.

A hypothesis is a tentative explanation for an observation. A scientific theory is a well-tested and consistently verified explanation for a set of observations or phenomena. A scientific law is a description, often in the form of a mathematical formula, of the behavior of an aspect of nature under certain circumstances. Two types of logical reasoning are used in science. Inductive reasoning uses results to produce general scientific principles. Deductive reasoning is a form of logical thinking that predicts results by applying general principles. The common thread throughout scientific research is the use of the scientific method. Scientists present their results in peer-reviewed scientific papers published in scientific journals.

Science can be basic or applied. The main goal of basic science is to expand knowledge without any expectation of short-term practical application of that knowledge. The primary goal of applied research, however, is to solve practical problems.

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This glossary is intended to assist you in understanding commonly used terms and concepts when reading, interpreting, and evaluating scholarly research. Also included are common words and phrases defined within the context of how they apply to research in the social and behavioral sciences.

• Acculturation -- refers to the process of adapting to another culture, particularly in reference to blending in with the majority population [e.g., an immigrant adopting American customs]. However, acculturation also implies that both cultures add something to one another, but still remain distinct groups unto themselves.
• Accuracy -- a term used in survey research to refer to the match between the target population and the sample.
• Affective Measures -- procedures or devices used to obtain quantified descriptions of an individual's feelings, emotional states, or dispositions.
• Aggregate -- a total created from smaller units. For instance, the population of a county is an aggregate of the populations of the cities, rural areas, etc. that comprise the county. As a verb, it refers to total data from smaller units into a large unit.
• Anonymity -- a research condition in which no one, including the researcher, knows the identities of research participants.
• Baseline -- a control measurement carried out before an experimental treatment.
• Behaviorism -- school of psychological thought concerned with the observable, tangible, objective facts of behavior, rather than with subjective phenomena such as thoughts, emotions, or impulses. Contemporary behaviorism also emphasizes the study of mental states such as feelings and fantasies to the extent that they can be directly observed and measured.
• Beliefs -- ideas, doctrines, tenets, etc. that are accepted as true on grounds which are not immediately susceptible to rigorous proof.
• Benchmarking -- systematically measuring and comparing the operations and outcomes of organizations, systems, processes, etc., against agreed upon "best-in-class" frames of reference.
• Bias -- a loss of balance and accuracy in the use of research methods. It can appear in research via the sampling frame, random sampling, or non-response. It can also occur at other stages in research, such as while interviewing, in the design of questions, or in the way data are analyzed and presented. Bias means that the research findings will not be representative of, or generalizable to, a wider population.
• Case Study -- the collection and presentation of detailed information about a particular participant or small group, frequently including data derived from the subjects themselves.
• Causal Hypothesis -- a statement hypothesizing that the independent variable affects the dependent variable in some way.
• Causal Relationship -- the relationship established that shows that an independent variable, and nothing else, causes a change in a dependent variable. It also establishes how much of a change is shown in the dependent variable.
• Causality -- the relation between cause and effect.
• Central Tendency -- any way of describing or characterizing typical, average, or common values in some distribution.
• Chi-square Analysis -- a common non-parametric statistical test which compares an expected proportion or ratio to an actual proportion or ratio.
• Claim -- a statement, similar to a hypothesis, which is made in response to the research question and that is affirmed with evidence based on research.
• Classification -- ordering of related phenomena into categories, groups, or systems according to characteristics or attributes.
• Cluster Analysis -- a method of statistical analysis where data that share a common trait are grouped together. The data is collected in a way that allows the data collector to group data according to certain characteristics.
• Cohort Analysis -- group by group analytic treatment of individuals having a statistical factor in common to each group. Group members share a particular characteristic [e.g., born in a given year] or a common experience [e.g., entering a college at a given time].
• Confidentiality -- a research condition in which no one except the researcher(s) knows the identities of the participants in a study. It refers to the treatment of information that a participant has disclosed to the researcher in a relationship of trust and with the expectation that it will not be revealed to others in ways that violate the original consent agreement, unless permission is granted by the participant.
• Confirmability Objectivity -- the findings of the study could be confirmed by another person conducting the same study.
• Construct -- refers to any of the following: something that exists theoretically but is not directly observable; a concept developed [constructed] for describing relations among phenomena or for other research purposes; or, a theoretical definition in which concepts are defined in terms of other concepts. For example, intelligence cannot be directly observed or measured; it is a construct.
• Construct Validity -- seeks an agreement between a theoretical concept and a specific measuring device, such as observation.
• Constructivism -- the idea that reality is socially constructed. It is the view that reality cannot be understood outside of the way humans interact and that the idea that knowledge is constructed, not discovered. Constructivists believe that learning is more active and self-directed than either behaviorism or cognitive theory would postulate.
• Content Analysis -- the systematic, objective, and quantitative description of the manifest or latent content of print or nonprint communications.
• Context Sensitivity -- awareness by a qualitative researcher of factors such as values and beliefs that influence cultural behaviors.
• Control Group -- the group in an experimental design that receives either no treatment or a different treatment from the experimental group. This group can thus be compared to the experimental group.
• Controlled Experiment -- an experimental design with two or more randomly selected groups [an experimental group and control group] in which the researcher controls or introduces the independent variable and measures the dependent variable at least two times [pre- and post-test measurements].
• Correlation -- a common statistical analysis, usually abbreviated as r, that measures the degree of relationship between pairs of interval variables in a sample. The range of correlation is from -1.00 to zero to +1.00. Also, a non-cause and effect relationship between two variables.
• Covariate -- a product of the correlation of two related variables times their standard deviations. Used in true experiments to measure the difference of treatment between them.
• Credibility -- a researcher's ability to demonstrate that the object of a study is accurately identified and described based on the way in which the study was conducted.
• Critical Theory -- an evaluative approach to social science research, associated with Germany's neo-Marxist “Frankfurt School,” that aims to criticize as well as analyze society, opposing the political orthodoxy of modern communism. Its goal is to promote human emancipatory forces and to expose ideas and systems that impede them.
• Data -- factual information [as measurements or statistics] used as a basis for reasoning, discussion, or calculation.
• Data Mining -- the process of analyzing data from different perspectives and summarizing it into useful information, often to discover patterns and/or systematic relationships among variables.
• Data Quality -- this is the degree to which the collected data [results of measurement or observation] meet the standards of quality to be considered valid [trustworthy] and  reliable [dependable].
• Deductive -- a form of reasoning in which conclusions are formulated about particulars from general or universal premises.
• Dependability -- being able to account for changes in the design of the study and the changing conditions surrounding what was studied.
• Dependent Variable -- a variable that varies due, at least in part, to the impact of the independent variable. In other words, its value “depends” on the value of the independent variable. For example, in the variables “gender” and “academic major,” academic major is the dependent variable, meaning that your major cannot determine whether you are male or female, but your gender might indirectly lead you to favor one major over another.
• Deviation -- the distance between the mean and a particular data point in a given distribution.
• Discourse Community -- a community of scholars and researchers in a given field who respond to and communicate to each other through published articles in the community's journals and presentations at conventions. All members of the discourse community adhere to certain conventions for the presentation of their theories and research.
• Discrete Variable -- a variable that is measured solely in whole units, such as, gender and number of siblings.
• Distribution -- the range of values of a particular variable.
• Effect Size -- the amount of change in a dependent variable that can be attributed to manipulations of the independent variable. A large effect size exists when the value of the dependent variable is strongly influenced by the independent variable. It is the mean difference on a variable between experimental and control groups divided by the standard deviation on that variable of the pooled groups or of the control group alone.
• Emancipatory Research -- research is conducted on and with people from marginalized groups or communities. It is led by a researcher or research team who is either an indigenous or external insider; is interpreted within intellectual frameworks of that group; and, is conducted largely for the purpose of empowering members of that community and improving services for them. It also engages members of the community as co-constructors or validators of knowledge.
• Empirical Research -- the process of developing systematized knowledge gained from observations that are formulated to support insights and generalizations about the phenomena being researched.
• Epistemology -- concerns knowledge construction; asks what constitutes knowledge and how knowledge is validated.
• Ethnography -- method to study groups and/or cultures over a period of time. The goal of this type of research is to comprehend the particular group/culture through immersion into the culture or group. Research is completed through various methods but, since the researcher is immersed within the group for an extended period of time, more detailed information is usually collected during the research.
• Expectancy Effect -- any unconscious or conscious cues that convey to the participant in a study how the researcher wants them to respond. Expecting someone to behave in a particular way has been shown to promote the expected behavior. Expectancy effects can be minimized by using standardized interactions with subjects, automated data-gathering methods, and double blind protocols.
• External Validity -- the extent to which the results of a study are generalizable or transferable.
• Factor Analysis -- a statistical test that explores relationships among data. The test explores which variables in a data set are most related to each other. In a carefully constructed survey, for example, factor analysis can yield information on patterns of responses, not simply data on a single response. Larger tendencies may then be interpreted, indicating behavior trends rather than simply responses to specific questions.
• Field Studies -- academic or other investigative studies undertaken in a natural setting, rather than in laboratories, classrooms, or other structured environments.
• Focus Groups -- small, roundtable discussion groups charged with examining specific topics or problems, including possible options or solutions. Focus groups usually consist of 4-12 participants, guided by moderators to keep the discussion flowing and to collect and report the results.
• Framework -- the structure and support that may be used as both the launching point and the on-going guidelines for investigating a research problem.
• Generalizability -- the extent to which research findings and conclusions conducted on a specific study to groups or situations can be applied to the population at large.
• Grey Literature -- research produced by organizations outside of commercial and academic publishing that publish materials, such as, working papers, research reports, and briefing papers.
• Grounded Theory -- practice of developing other theories that emerge from observing a group. Theories are grounded in the group's observable experiences, but researchers add their own insight into why those experiences exist.
• Group Behavior -- behaviors of a group as a whole, as well as the behavior of an individual as influenced by his or her membership in a group.
• Hypothesis -- a tentative explanation based on theory to predict a causal relationship between variables.
• Independent Variable -- the conditions of an experiment that are systematically manipulated by the researcher. A variable that is not impacted by the dependent variable, and that itself impacts the dependent variable. In the earlier example of "gender" and "academic major," (see Dependent Variable) gender is the independent variable.
• Individualism -- a theory or policy having primary regard for the liberty, rights, or independent actions of individuals.
• Inductive -- a form of reasoning in which a generalized conclusion is formulated from particular instances.
• Inductive Analysis -- a form of analysis based on inductive reasoning; a researcher using inductive analysis starts with answers, but formulates questions throughout the research process.
• Insiderness -- a concept in qualitative research that refers to the degree to which a researcher has access to and an understanding of persons, places, or things within a group or community based on being a member of that group or community.
• Internal Consistency -- the extent to which all questions or items assess the same characteristic, skill, or quality.
• Internal Validity -- the rigor with which the study was conducted [e.g., the study's design, the care taken to conduct measurements, and decisions concerning what was and was not measured]. It is also the extent to which the designers of a study have taken into account alternative explanations for any causal relationships they explore. In studies that do not explore causal relationships, only the first of these definitions should be considered when assessing internal validity.
• Life History -- a record of an event/events in a respondent's life told [written down, but increasingly audio or video recorded] by the respondent from his/her own perspective in his/her own words. A life history is different from a "research story" in that it covers a longer time span, perhaps a complete life, or a significant period in a life.
• Margin of Error -- the permittable or acceptable deviation from the target or a specific value. The allowance for slight error or miscalculation or changing circumstances in a study.
• Measurement -- process of obtaining a numerical description of the extent to which persons, organizations, or things possess specified characteristics.
• Meta-Analysis -- an analysis combining the results of several studies that address a set of related hypotheses.
• Methodology -- a theory or analysis of how research does and should proceed.
• Methods -- systematic approaches to the conduct of an operation or process. It includes steps of procedure, application of techniques, systems of reasoning or analysis, and the modes of inquiry employed by a discipline.
• Mixed-Methods -- a research approach that uses two or more methods from both the quantitative and qualitative research categories. It is also referred to as blended methods, combined methods, or methodological triangulation.
• Modeling -- the creation of a physical or computer analogy to understand a particular phenomenon. Modeling helps in estimating the relative magnitude of various factors involved in a phenomenon. A successful model can be shown to account for unexpected behavior that has been observed, to predict certain behaviors, which can then be tested experimentally, and to demonstrate that a given theory cannot account for certain phenomenon.
• Models -- representations of objects, principles, processes, or ideas often used for imitation or emulation.
• Naturalistic Observation -- observation of behaviors and events in natural settings without experimental manipulation or other forms of interference.
• Norm -- the norm in statistics is the average or usual performance. For example, students usually complete their high school graduation requirements when they are 18 years old. Even though some students graduate when they are younger or older, the norm is that any given student will graduate when he or she is 18 years old.
• Null Hypothesis -- the proposition, to be tested statistically, that the experimental intervention has "no effect," meaning that the treatment and control groups will not differ as a result of the intervention. Investigators usually hope that the data will demonstrate some effect from the intervention, thus allowing the investigator to reject the null hypothesis.
• Ontology -- a discipline of philosophy that explores the science of what is, the kinds and structures of objects, properties, events, processes, and relations in every area of reality.
• Panel Study -- a longitudinal study in which a group of individuals is interviewed at intervals over a period of time.
• Participant -- individuals whose physiological and/or behavioral characteristics and responses are the object of study in a research project.
• Peer-Review -- the process in which the author of a book, article, or other type of publication submits his or her work to experts in the field for critical evaluation, usually prior to publication. This is standard procedure in publishing scholarly research.
• Phenomenology -- a qualitative research approach concerned with understanding certain group behaviors from that group's point of view.
• Philosophy -- critical examination of the grounds for fundamental beliefs and analysis of the basic concepts, doctrines, or practices that express such beliefs.
• Phonology -- the study of the ways in which speech sounds form systems and patterns in language.
• Policy -- governing principles that serve as guidelines or rules for decision making and action in a given area.
• Policy Analysis -- systematic study of the nature, rationale, cost, impact, effectiveness, implications, etc., of existing or alternative policies, using the theories and methodologies of relevant social science disciplines.
• Population -- the target group under investigation. The population is the entire set under consideration. Samples are drawn from populations.
• Position Papers -- statements of official or organizational viewpoints, often recommending a particular course of action or response to a situation.
• Positivism -- a doctrine in the philosophy of science, positivism argues that science can only deal with observable entities known directly to experience. The positivist aims to construct general laws, or theories, which express relationships between phenomena. Observation and experiment is used to show whether the phenomena fit the theory.
• Predictive Measurement -- use of tests, inventories, or other measures to determine or estimate future events, conditions, outcomes, or trends.
• Principal Investigator -- the scientist or scholar with primary responsibility for the design and conduct of a research project.
• Probability -- the chance that a phenomenon will occur randomly. As a statistical measure, it is shown as p [the "p" factor].
• Questionnaire -- structured sets of questions on specified subjects that are used to gather information, attitudes, or opinions.
• Random Sampling -- a process used in research to draw a sample of a population strictly by chance, yielding no discernible pattern beyond chance. Random sampling can be accomplished by first numbering the population, then selecting the sample according to a table of random numbers or using a random-number computer generator. The sample is said to be random because there is no regular or discernible pattern or order. Random sample selection is used under the assumption that sufficiently large samples assigned randomly will exhibit a distribution comparable to that of the population from which the sample is drawn. The random assignment of participants increases the probability that differences observed between participant groups are the result of the experimental intervention.
• Reliability -- the degree to which a measure yields consistent results. If the measuring instrument [e.g., survey] is reliable, then administering it to similar groups would yield similar results. Reliability is a prerequisite for validity. An unreliable indicator cannot produce trustworthy results.
• Representative Sample -- sample in which the participants closely match the characteristics of the population, and thus, all segments of the population are represented in the sample. A representative sample allows results to be generalized from the sample to the population.
• Rigor -- degree to which research methods are scrupulously and meticulously carried out in order to recognize important influences occurring in an experimental study.
• Sample -- the population researched in a particular study. Usually, attempts are made to select a "sample population" that is considered representative of groups of people to whom results will be generalized or transferred. In studies that use inferential statistics to analyze results or which are designed to be generalizable, sample size is critical, generally the larger the number in the sample, the higher the likelihood of a representative distribution of the population.
• Sampling Error -- the degree to which the results from the sample deviate from those that would be obtained from the entire population, because of random error in the selection of respondent and the corresponding reduction in reliability.
• Saturation -- a situation in which data analysis begins to reveal repetition and redundancy and when new data tend to confirm existing findings rather than expand upon them.
• Semantics -- the relationship between symbols and meaning in a linguistic system. Also, the cuing system that connects what is written in the text to what is stored in the reader's prior knowledge.
• Social Theories -- theories about the structure, organization, and functioning of human societies.
• Sociolinguistics -- the study of language in society and, more specifically, the study of language varieties, their functions, and their speakers.
• Standard Deviation -- a measure of variation that indicates the typical distance between the scores of a distribution and the mean; it is determined by taking the square root of the average of the squared deviations in a given distribution. It can be used to indicate the proportion of data within certain ranges of scale values when the distribution conforms closely to the normal curve.
• Statistical Analysis -- application of statistical processes and theory to the compilation, presentation, discussion, and interpretation of numerical data.
• Statistical Bias -- characteristics of an experimental or sampling design, or the mathematical treatment of data, that systematically affects the results of a study so as to produce incorrect, unjustified, or inappropriate inferences or conclusions.
• Statistical Significance -- the probability that the difference between the outcomes of the control and experimental group are great enough that it is unlikely due solely to chance. The probability that the null hypothesis can be rejected at a predetermined significance level [0.05 or 0.01].
• Statistical Tests -- researchers use statistical tests to make quantitative decisions about whether a study's data indicate a significant effect from the intervention and allow the researcher to reject the null hypothesis. That is, statistical tests show whether the differences between the outcomes of the control and experimental groups are great enough to be statistically significant. If differences are found to be statistically significant, it means that the probability [likelihood] that these differences occurred solely due to chance is relatively low. Most researchers agree that a significance value of .05 or less [i.e., there is a 95% probability that the differences are real] sufficiently determines significance.
• Subcultures -- ethnic, regional, economic, or social groups exhibiting characteristic patterns of behavior sufficient to distinguish them from the larger society to which they belong.
• Testing -- the act of gathering and processing information about individuals' ability, skill, understanding, or knowledge under controlled conditions.
• Theory -- a general explanation about a specific behavior or set of events that is based on known principles and serves to organize related events in a meaningful way. A theory is not as specific as a hypothesis.
• Treatment -- the stimulus given to a dependent variable.
• Trend Samples -- method of sampling different groups of people at different points in time from the same population.
• Triangulation -- a multi-method or pluralistic approach, using different methods in order to focus on the research topic from different viewpoints and to produce a multi-faceted set of data. Also used to check the validity of findings from any one method.
• Unit of Analysis -- the basic observable entity or phenomenon being analyzed by a study and for which data are collected in the form of variables.
• Validity -- the degree to which a study accurately reflects or assesses the specific concept that the researcher is attempting to measure. A method can be reliable, consistently measuring the same thing, but not valid.
• Variable -- any characteristic or trait that can vary from one person to another [race, gender, academic major] or for one person over time [age, political beliefs].
• Weighted Scores -- scores in which the components are modified by different multipliers to reflect their relative importance.
• White Paper -- an authoritative report that often states the position or philosophy about a social, political, or other subject, or a general explanation of an architecture, framework, or product technology written by a group of researchers. A white paper seeks to contain unbiased information and analysis regarding a business or policy problem that the researchers may be facing.

Elliot, Mark, Fairweather, Ian, Olsen, Wendy Kay, and Pampaka, Maria. A Dictionary of Social Research Methods. Oxford, UK: Oxford University Press, 2016; Free Social Science Dictionary. Socialsciencedictionary.com [2008]. Glossary. Institutional Review Board. Colorado College; Glossary of Key Terms. Writing@CSU. Colorado State University; Glossary A-Z. Education.com; Glossary of Research Terms. Research Mindedness Virtual Learning Resource. Centre for Human Servive Technology. University of Southampton; Miller, Robert L. and Brewer, John D. The A-Z of Social Research: A Dictionary of Key Social Science Research Concepts London: SAGE, 2003; Jupp, Victor. The SAGE Dictionary of Social and Cultural Research Methods . London: Sage, 2006.

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Meaning of hypothesis in English

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• abstraction
• afterthought
• anthropocentrism
• anti-Darwinian
• exceptionalism
• foundation stone
• great minds think alike idiom
• non-dogmatic
• non-empirical
• non-material
• non-practical
• social Darwinism
• supersensible
• the domino theory

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