STA 135 Multivariate Data Analysis
Lecture: 3 hours
Discussion: 1 hour
Multivariate normal distribution; Mahalanobis distance; sampling distributions of the mean vector and covariance matrix; Hotellings T2; simultaneous inference; one-way MANOVA; discriminant analysis; principal components; canonical correlation; factor analysis. Intensive use of computer analyses and real data sets.
Prerequisite: STA 130B or STA 131B; MAT 022A or MAT 067
Summary of course contents:
Applied Multivariate Statistical Analysis by Johnson and Wichern