This data-driven doctoral seminar will provide the skills needed to perform advanced multivariate data analysis by incorporating current techniques. Topics covered will include assumptions and limitations, multivariate data collection, pre-analysis data screening, factorial and multivariate analysis of variance and covariance, linear and non-linear multiple regressions, path analysis, exploratory factor analysis, confirmatory factor analysis, and structural equation models (SEM). Students will be provided with datasets for data analyses of the multivariate methods discussed in seminar along with scholarly articles that make use of the multivariate methods discussed. Students will be introduced to the use of SPSS and other advanced multivariate tools. Prerequisite/s: RESD 0700 or RESD 0705