Dr. Ray L. Winstead
IUP Professor of Biology

Definitions in Statistics


           1. Independent Variable: An independent variable is any variable that is assumed to produce an effect on, or be related to, a behavior of interest - - or - - the independent variable is the variable manipulated by the experimenter. The level of the independent variable is simply a particular value of the independent variable.

           2. Dependent Variable: The dependent variable is the measure of the behavior that the researcher observes but does not manipulate or control.

           3. Type of dependent variable:

Score data: Each subject is assigned a numerical score that represents its performance or behavior. This type of dependent variable includes data on a ratio scale where the scale has constant interval size plus a true zero (e.g., weight) and also data on an interval scale where the scale has constant interval size but not a true zero (e.g., degrees C or degrees F)

Ordered data = Ordinal data: Each subject is assigned a rank that represents its position along some ordered dimension.

Frequency data = Nominal data: Each subject is counted as being in a particular classification, or cross-classification, of categories.

         4. Between-subjects design: In a between-subjects design, all comparisons between different conditions (groups) are based on comparisons between different subjects.

         5. Within-subjects design: In a within-subjects design, all comparisons between different conditions (groups) are based on comparisons within the same group of subjects.

         6. Mixed design: A combination of a between-subjects comparison and within-subjects comparison in the same experiment.


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Dr. Ray L. Winstead
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