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F&ES 758 01 (23581) /STAT660/STAT363
Multivariate Statistical Analysis in the Environmental Sciences
Jonathan Reuning-Scherer
TTh 1.00-2.15 KRN 301
Spring 2013 
3 credits. An introduction to the analysis of multivariate data. Topics include multivariate analysis of variance (MANOVA), principal components analysis, cluster analysis (hierarchical clustering, k-means), canonical correlation, multidimensional scaling ordination methods, discriminate analysis, and structural equations modeling. Emphasis is placed on practical application of multivariate techniques to a variety of natural and social examples in the environmental sciences. Students are required to select a dataset early in the term for use throughout the term. There are regular assignments and a final project. Extensive use of computers is required. Three hours lecture/discussion.
Prerequisite: a prior course in introductory statistics.