It is argued that, given the importance and the increased use of multivariate techniques such as factor analysis and canonical correlation, students need to be made aware of multivariate methods and the appropriate ways in which they can be applied. As a general linear model that subsumes all other parametric measures, canonical correlation analysis provides a natural framework for instruction involving all of the various parametric procedures (e.g., analysis of variance and analysis of covariance). Furthermore, when canonical correlation analysis is used as an instructional tool, students gain an understanding of how all parametric procedures are special cases of canonical correlation analysis, that all parametric procedures involve the application of weights to derive synthetic scores, and that all parametric procedures are correlational, thus yielding a measure of effect that is important to the interpretation of one's results. A small heuristic data set (18 examples) is used to demonstrate how canonical correlation analysis can be used as an instructional device in teaching both univariate and multivariate parametric methods. Fourteen tables present data from the example and illustrate the discussion through comparison of analytic techniques. A 30-item list of references and 1 appendix are included. (Author/SLD)