This is a traditional course in multivariate statistical methods, covering the multivariate normal distribution with inference of mean vectors, principal component analysis, factor analysis and canonical correlation analysis. The course requires good knowledge of matrix algebra and undergraduate courses in statistical inference and linear statistical models.
The course is intended for students in the Masters program Statistics and Data Mining as a profile course in Statistics.
Course literature: The course will be based on
Johnson, R.A. & Wichern, D.W.: Applied Multivariate Statistical Analysis, Sixth Ed. ISBN: 0-13-514350-0