Although there is a healthy trend toward employment of multivariate statistical methods in the analysis of data from experiments in psychology and education which involve multiple dependent variables, there remains a need to demonstrate the wide variety of data analytic techniques available for post hoc analysis of statistically significant multivariate results. This paper attempts to: (1) clearly illustrate the use of six pertinent statistical analysis methods on a common sample data set; (2) compare the results both in terms of sensitivity to the treatment differences and interpretive clarity with respect to the research hypothesis; and (3) present guidelines to the applied researcher for selecting among the alternatives in a particular research context. Post hoc data analytic methods presented are: univariate F tests, univariate multiple comparison methods, step-down F tests, linear discriminant analysis, multiple profile analysis, and multivariate simultaneous test procedures. (Author/PN)