Description
This course introduces graduate students to multivariate statistics, overview of univariate and bivariate statistics, screening
of data including issues of normality, linearity, homoscedasticity, multiple regression, canonical correlations, analysis of
covariance, multiple analysis of variance and covariance, profile analysis, logistic regression, principle components and
factor analysis, and introduction to structural equation modeling. Prerequisite: FPY 500. (3 units; Spring)