The purpose of this module is to provide the researcher and the consumers of such research with a recognition of the assumptions and appropriate use and interpretation of each of 10 multiple comparison (MC) statistical techniques. In this self-contained and self-instructional module, the user is sensitized to the serious consequences of inappropriate multiple comparison use by employing all MC methods to the same data. He then is introduced to the criteria for selecting the best MC method for a given purpose. Computational considerations follow with self-instructional exercises and mastery tests. A familiarity with the t-test and one-factor analysis of variance is required. (Author/SE)