Thomas T. John, Ph.D.
Adjunct Faculty – Syracuse University
Consultant – Statistics & Business Intelligence
215 Carnegie Hall
Syracuse University
Syracuse, NY 13244
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2013 Spring — MAT 755 – Multivariate Statistical Analysis

Instructor: Thomas John, Ph.D.
Carnegie 219A, 443-1587(office), 443-3849(message/math-dept), thjohn at syr dot edu.
Class: Tue & Thu 9:30 AM – 10:50 AM in Carnegie 311.
Office Hours: Tue & Thu 2:00-3:00 PM, and by appointment.
Text: Applied Multivariate Statistical Analysis, by Richard A. Johnson and Dean W. Wichern, 6th edition,
ISBN-13: 978-0-13-187715-3.
Course Description: (per course catalogue: Multivariate normal distribution, conditional densities, partial correlation, multiple correlation, regression coefficients, maximum likelihood estimates, Hotelling’s statistic, Wishart distribution, tests of hypotheses, and linear discriminant functions.)
Analysis of multivariate observations will be covered with equal emphasis on theory and examples. Course will begin with reviews of concepts needed from linear algebra and mathematical statistics. Then the course will proceed through important multivariate sampling distributions and multivariate inference procedures. The latter part of the semester will focus on applications of multivariate methods such as principal component analysis, factor analysis, clustering, and classification.
R statistical software (http://www.r-project.org) will be used for computations.

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