Prerequisites: Level V statistics or permission of instructor. Methods for reduction of dimensionality, including principal components analysis, factor analysis, and multidimensional scaling; correlation techniques, including partial, multiple and canonical correlation; classification and clustering methods. Emphasis on data analytic issues, concepts and methods (e.g., graphical techniques) and on applications drawn from several areas, including behavioral, management, physical and engineering sciences
