Statistics

ST731 - Applied Multivariate Statistical Analysis

• Prerequisites: ST512
• Term & Frequency: Spring each year
• Student Audience: MS and PhD students (both statistics and non-stat majors)
• Credit: 3 credits
• Recent Texts: Applied Multivariate Statistical Analysis, by Richard Johnson and Dean Wichern, 6th edition, Pearson Prentice Hall
• Recent Instructors: Arnab Maity, Lexin Li
• Background and Goals: An introduction to use of multivariate statistical methods in analysis of data collected in experiments and surveys. Students will (a) be capable of selecting, carrying out and interpreting appropriate statistical methods for describing and analyzing multivariate data sets, in the context of their own research interests; (b) have an appreciation of a range of multivariate methods and their use and limitations in a research context; (c) be able to examine critically their own and other researchers’ use of methods of analysis for multivariate data. Emphasis upon use of a computer to perform multivariate statistical analysis calculations.
• Content: Multivariate normal distribution, Inferences about a mean vector, Comparison of several multivariate means, Principal components analysis, Factor analysis, Canonical correlation analysis, Discrimination and classification, Clustering
• Alternatives: NOne
• Subsequent Courses: None

SP 2013 Sections: