Multivariate statistics will prepare students to understand multivariate statistical methods and draw the link between statistics previously learned. Students will be able to conduct, interpret, and critique procedures such as factorial ANOVA, multiple regression, MANOVA, ANCOVA, MANCOVA, PCA, EFA, discriminant function analysis, logistic, regression, canonical correlation, hierarchical linear regression, and multivariate analysis of change. Become familiar with statistical software for implementing multivariate procedures. Develop an understanding of the concepts, terms, and symbols used in multivariate statistics (e.g. Matrix Algebra, effect sizes). Gain an appreciation of the role of multivariate procedures in the research process. Gain requisite knowledge necessary to learn more complex statistical procedures.

Multivariate statistics will prepare students to understand multivariate statistical methods and draw the link between statistics previously learned. Students will be able to conduct, interpret, and critique procedures such as factorial ANOVA, multiple regression, MANOVA, ANCOVA, MANCOVA, PCA, EFA, discriminant function analysis, logistic, regression, canonical correlation, hierarchical linear regression, and multivariate analysis of change. Become familiar with statistical software for implementing multivariate procedures. Develop an understanding of the concepts, terms, and symbols used in multivariate statistics (e.g. Matrix Algebra, effect sizes). Gain an appreciation of the role of multivariate procedures in the research process. Gain requisite knowledge necessary to learn more complex statistical procedures.