Dependent Variable

In a scientific experiment, a researcher investigates whether changes in one or more independent variables have an effect on one or more dependent variables. A dependent variable is what is assessed as an outcome or effect of the study. It is a variable because the measure can take on some range of values. It is called dependent because it is hypothesized to be affected by changes in the independent variable. The direction of the presumed effect is always the same: from the independent variable to the dependent variable.

For example, suppose that a researcher is interested in whether noise distracts children from efficient processing of information. A relevant experiment might involve testing children in three conditions: silence, mild noise, and moderately loud noise. The test might involve presenting a series of test trials in which each child is shown a set of digits (numbers), presented one at a time. After each set, the child is asked to say aloud as many as possible of the digits in that set, in the order presented. Some of the trials would occur with silence in the testing room, other trials would occur with some mild amount of background noise in the room, and other trials would occur with moderately loud background noise. In this experiment, the dependent variable is the outcome measure, namely, the number of digits correctly recalled. The researcher might hypothesize that the children would recall the most digits in the silent condition and the least digits in the moderate noise condition. If these results occurred, the researcher would conclude that the independent variable (noise condition) caused changes in the dependent variable (digit memory).

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There are many kinds of measures that can function as dependent variables in psychological studies. A dependent variable can be a measure of behavior, such as performance on a test or reaction time to a stimulus. It can be a self-report measure, such as responses on a personality or attitude assessment. It can be a physiological measure, such as a change in brain waves or in levels of a hormone.

Dependent variables must be identified by examining the design of an experiment. That is, some variables could potentially function as independent or dependent variables, depending on the proposed pattern of cause and effect and on the way the variables are used in the experiment. For example, sugar consumption might be an independent variable in a study where you examine the effects of sugar on memory abilities by varying and controlling the amount of sugar  eaten  by  groups  of  people  over  some  time period and testing their memories. Sugar consumption might be a dependent variable in a study in which you compare a group of children who received specific nutritional classes to a control group of children who did not receive such classes, and you subsequently measure the amount of sugar consumed.

In selecting a dependent variable, researchers must consider the reliability and validity of the measure.

Reliability refers to whether the measure has stability. That is, if the study were repeated, would the measure be similar? If other responses that assessed the same task were used, would those measures show a similar response pattern to the initial measure used? Validity refers to whether the measure accurately reflects what was intended to be tested. For example, infant’s attention may be operationally defined by the dependent variable of looking duration, as long as there is reason to argue that looking time accurately reflects infants’ attention.


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