Canonical correlation analysis explores the relationship between two sets of variables. It is a sophisticated multivariate technique that subsumes all parametric methods. In other words, all parametric methods are special cases of canonical correlation analysis. The instruction of canonical correlation analysis facilitates students to see that all parametric methods involve the creation of synthetic scores for each subject. The synthetic scores are the focus for analysis. The purpose of the present paper is to employ a real data set to demonstrate how canonical correlation analysis yields results the same as those results from other parametric methods. The parametric methods used in this paper are as follows: (1) Pearson product-moment correlation; (2) t-test; (3) two-way analysis of variane; (4) one-way analysis of covariance; (5) one-way multivariate analysis of variance; (6) two-way multivariate analysis of variance; (7) multiple regression analysis; (8) discriminant analysis; (9) chi-square test (nonparemetric method).