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Common demand characteristics include: Rumors of the study – any information, true or false, circulated about the experiment outside of the experiment itself.; Setting of the laboratory – the location where the experiment is being performed, if it is significant.
An example of a descriptive device used in psychological research is the diary, which is used to record observations. There is a history of use of diaries within clinical psychology. [20] Examples of psychologists that used them include B.F. Skinner (1904–1990) and Virginia Axline (1911–1988).
The variables made to remain constant during an experiment are referred to as control variables. For example, if an outdoor experiment were to be conducted to compare how different wing designs of a paper airplane (the independent variable) affect how far it can fly (the dependent variable), one would want to ensure that the experiment is ...
For example, in a study examining the effect of post-secondary education on lifetime earnings, some extraneous variables might be gender, ethnicity, social class, genetics, intelligence, age, and so forth. A variable is extraneous only when it can be assumed (or shown) to influence the dependent variable.
In the examples listed above, a nuisance variable is a variable that is not the primary focus of the study but can affect the outcomes of the experiment. [3] They are considered potential sources of variability that, if not controlled or accounted for, may confound the interpretation between the independent and dependent variables .
The matching law can be applied to situations involving a single response maintained by a single schedule of reinforcement if one assumes that alternative responses are always available to an organism, maintained by uncontrolled "extraneous" reinforcers. For example, an animal pressing a lever for food might pause for a drink of water.
A variable in an experiment which is held constant in order to assess the relationship between multiple variables [a], is a control variable. [2] [3] A control variable is an element that is not changed throughout an experiment because its unchanging state allows better understanding of the relationship between the other variables being tested. [4]
Confounding is defined in terms of the data generating model. Let X be some independent variable, and Y some dependent variable.To estimate the effect of X on Y, the statistician must suppress the effects of extraneous variables that influence both X and Y.