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DS 6320
Multivariate Statistics
Three semester hours.
Business data frequently measure more than one aspect; that is, it is multivariate. The objective of this course is to introduce powerful methods for understanding and obtaining managerial insight from multivariate data. Multivariate methods studied in the course include a selection of principle component analysis, factor analysis, canonical correlation, discriminate analysis, multidimensional scaling, cluster analysis, and neural nets. Readings, cases, examples and exercises are drawn from diverse areas of business. Prerequisite: Consent of the instructor and the Graduate Advisor.

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