Find definitions for the terminology used throughout the Understanding Science pages.
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To take as the best explanation based on the evidence. In the scientific community, an idea is generally accepted when it is supported by many lines of evidence and meets other criteria (e.g., consistency with well-established ideas in related fields). To learn more about how and why scientific ideas are accepted, visit Competing ideas: A perfect fit for the evidence. To learn more about the difference between acceptance and belief, visit our misconception on the topic.
In science, an observation that differs from the expectations generated by an established scientific idea. Anomalous observations may inspire scientists to reconsider, modify, or come up with alternatives to an accepted theory or hypothesis.
Research undertaken with the explicit goal of solving a problem or developing a technology. The boundary between pure and applied science is fuzzy. Research undertaken in the pure pursuit of knowledge often ends up having useful applications, and research begun with an application in mind often ends up informing our understanding of the natural world more broadly.
In science, an auxiliary hypothesis that is taken as true for the purposes of interpreting a particular test. All tests involve making assumptions. If an assumption of a test turns out to be inaccurate, it can cause the test results to be incorrectly interpreted. However, assumptions can be independently tested to help establish their accuracy. To learn more, visit Making assumptions.
Generally refers to a Pearson's chi-square test, which is a statistical test used to determine how well a set of whole-number data matches expectations. Chi-square tests are often used when a test outcome takes the form of a number of different sorts of events. For example, a chi-square test might be used to determine how closely the sex ratio among the offspring of a particular mating match the expectations generated by Mendel's laws or how closely the numbers rolled by a particular die match what we would expect if the die were fair. A chi-square test helps one figure out how likely a particular set of results are if a hypothesis (e.g., "Mendels laws apply" or "the die is fair") were true.
In science publishing, a reference to another published scientific work that provides the information necessary to locate that work. Through citations, the scientific community expects its members to give credit to the ideas, techniques, and studies of other scientists that influenced or informed a particular investigation. To learn more, visit Scientific culture: Great expectations.
In science publishing, to give credit to the previous work of other scientists usually through a list of references, or citations, at the end of a scientific article. Through citations, the scientific community expects its members to give credit to the ideas, techniques, and studies of other scientists that influenced or informed a particular investigation. To learn more, visit Scientific culture: Great expectations.
In medical research, a study that is carried out with human participants, as opposed to one that relies on animal models or in vitro experiments. Before new medical treatments reach clinical trials, they are usually studied using many other methods to try to establish their efficacy and safety.
In scientific testing, a group of individuals or cases matched to an experimental group and treated in the same way as that group, but which is not exposed to the experimental treatment or factor that the experimental group is. Control groups are especially important in medical studies in order to separate placebo effects from outcomes of interest. Control groups are sometimes also called control treatments or simply controls. This can be confusing since this use of the term is slightly different from what we mean when talking about controlled variables. To learn more, visit our side trip Fair tests in the field of medicine.
In scientific testing, to keep a variable or variables constant so that the impact of another factor can be better understood. To learn more, visit our side trip Designing fair tests.
An experiment that uses a control group. To learn more, visit our side trip Designing fair tests.
In scientific testing, a variable that is kept constant so that the impact of another factor can be better understood. This can be confusing because this use of the term is slightly different from what we mean when talking about control groups. To learn more, visit our side trip Designing fair tests. To learn more, visit our side trip Designing fair tests.
A relationship between two variables, such that the value of one variable can be used to generate an expectation about the value of the other. A correlation may occur because one variable is causally related to the other (e.g., cell phone use while driving may be correlated with auto accidents because speaking on the cell phone directly contributes to accidents) but correlations may also occur for other reasons. For example, it's possible that cell phone use and accident rates are correlated because people who are prone to getting in car accidents are more likely to spend a lot of time on cell phones. It's important to remember that a correlation between two variables does not necessarily mean that one causes the other.
Information gleaned from observations usually observations that are made in a standardized way. The term data generally refers to raw data information that has not yet been analyzed. Data (multiple pieces of information) is the plural form of datum (a single piece of information).
To figure out through logical reasoning. Deductions are often based on established knowledge and/or assumptions.
An experiment designed such that neither the participants nor the researchers observing them know which participants are in the experimental and control groups until after the observations are complete. Double-blind experiments are particularly important in the field of medicine because they control for both the placebo effect and unconscious bias on the part of the researchers two factors that can make the results of a medical study difficult to interpret. To learn more, visit our side trip Fair tests in the field of medicine.
In reference to statistics, the difference between a computed or measured value and the true value. To learn more, visit our misconception on the topic of error.
Test results and/or observations that may either help support or help refute a scientific idea. In general, raw data are considered evidence only once they have been interpreted in a way that reflects on the accuracy of a scientific idea.
In science, a potential outcome of a scientific test that is arrived at by logically reasoning about a particular scientific idea (i.e., what we would logically expect to observe if a given hypothesis or theory were true or false). The expectations generated by an idea are sometimes called its predictions. Observations that match the expectations generated by an idea are generally interpreted as supporting evidence. Mismatches are generally interpreted as contradictory evidence. To learn more about the relationship between expectations and observations, visit The core of science. To learn more about why this website uses the term expectation instead of prediction, visit our page on Misconceptions about science.
A scientific test that involves manipulating some factor or factors in a system in order to see how those changes affect the outcome or behavior of the system. Experiments are important in science, but they are not the only way to test scientific ideas. To learn more about the role of experiments in science, visit Tactics for testing ideas. To learn about experimental design, visit our side trip Designing fair tests.
In scientific testing, a group of individuals or cases that receive the experimental treatment or factor. Experimental groups can be contrasted with control groups.
Statement that is known to be true through direct observation. Since scientific ideas are inherently tentative, the term fact is more meaningful in everyday language than in the language of science. To learn more, visit our misconception on the topic.
A perceived or real media bias, in which opposing viewpoints are given similar weight though the evidence more strongly supports one viewpoint. To learn more, visit Beware of false balance.
To perform a test showing that a particular claim or scientific idea is false. The idea that science relies solely on falsification is based on Karl Popper's influential account of scientific justification, which suggests that science can only reject, or falsify, hypotheses that science cannot find evidence that supports one idea over others. In fact, science can never once-and-for-all prove that a particular idea is false (or true) and both supporting and refuting evidence may contribute to our evaluation of a scientific idea. To learn more, visit our misconception on the topic.
Government and private organizations, foundations, and other groups that provide scientists with the funds they need to do their research. To learn more, visit Supporting science.
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