System Analysis and Multivariate Statistics

Catalog description

Statistical analysis for data collected in several variables. Topics include sampling from multivariate normal distribution, multivariate analysis of variance, discriminant analysis, principal components, and factor analysis. This course will deal with methods and software to analyze multivariate data. The course begins with a quick review of basic statistics and a short introduction to essential linear algebra concepts. Then students will learn techniques for multivariate data and basic tools for multivariate analysis. Topics include regression in several variables, measuring and testing multivariable distances, principal components, factor analysis, cluster analysis, and multidimensional scaling. Students will do analysis and computations of data sets using the R- package, SPSS, and SAS packages.