PSYC 2530 Chapter Notes - Chapter 4: Squared Deviations From The Mean, Xg Technology, Standard Deviation

• School: York University
• Department: Psychology
• Course: PSYC 2530
• Professor: Anne Russon

Document Summary

Variability: provides a quantitative measure of the differences between scores in a distribution and describes the degree to which the scores are spread out or clustered together. A good measure of variability serves two purposes: 01. Specifically, it tells whether the scores are clustered close together or are spread out over a large distance. Usually, variability is defined in terms of distance. It tells how much distance to expect between one score and another, or how much distance to expect between an individual score and the mean: 02. Variability measures how well an individual score (or group of scores) represents the entire distribution. The aspect of variability is very important for inferential statistics, in which relatively small samples are used to answer questions about populations. Variability provides information about how much error to expect. We consider three different measures of variability: the range, standard deviation, and variance.