Multivariate statistical analyses are appropriate whenever a study involves two or more outcome variables. Because multiple-outcome models reflect social reality more accurately than do conventional single-outcome or univariate models, multivariate analysis should be studied and practiced more extensively than it is. In this article, several reasons for doing multivariate analysis are presented, and two common errors in statistical analysis are discussed. Examples are presented to show how a single multivariate analysis can produce different results than do separate univariate analyses, and to illustrate the relationship between ANOVA and canonical correlation analysis.