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.

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.

An experiment that uses a control group. To learn more, visit our side trip Designing fair tests.

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.

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 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 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 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.

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.