Basic concepts and applications of multivariate methods including: inferences about mean vectors and covariance matrices; multivariate regression; multivariate analysis of variance; data reduction using principal components, factor and cluster analysis; classification using discriminant analysis and logistic regression. Statistical software used.
Letter grade only (A-F). (Lecture 3 hrs.) Not open for credit to students with credit in MATH 483 or MATH 593.
