ABSTRACT
A common goal of multivariate statistical analysis is to determine and explain how groups of variables are related, and ultimately to develop theories of causation that can be traced to those relationships (Bernard 2000). Among the many multivariate procedures developed for data analysis are multiple regression analysis, partial regression, path analysis, multiple dimensional scaling, multiple analyses of variance and covariance, multiple discriminant analysis, factor and cluster analysis, and more. This chapter describes three major families of multivariate statistics: 1) multiple regression analysis, 2) the group–membership prediction and classification tool, Multiple Discriminant Analysis (MDS) and 3) factor analysis and cluster analysis for data reduction and statistically summarizing data sets.
