Applied Multivariate Statistics. 3 credits

Catalog description

Introduces a variety of multivariate statistical methods as aids to analyzing and interpreting large data sets. These methods will have general applications across a wide range of disciplines. Topics include: principal components analysis, cluster analysis, discriminant analysis, multi-dimensional scaling, correspondence analysis, and canonical correlation analysis. Extensive use of statistical software. Notes: Students may not receive credit for both STAT 462 and STAT 522 . Cannot be used to satisfy requirements for MS in Statistical Science. Offered by Statistics . May not be repeated for credit.