Multivariate Analysis

Postgraduate course

Course description

Objectives and Content

The course contains descriptive multivariate statistics, multivariate distribution theory such as the multinormal and the Wishart distribution. Furthermore, it contains multivariate t-tests, simultaneous confidence intervals, multivariate regression, principal components and factor analysis. In addition discriminant analysis, cluster analysis and correspondence analysis are mentioned. Finally, the spectral and singular value decomposition is discussed.

Learning Outcomes

The course gives an introduction to multivariate statistics with the emphasis on practical applications. The students get experience in using important methods through exercises with the software package S-plus.

Semester of Instruction

Irregular, course will be offered if it is on this course list: Workbook: Emneliste for innreisende utvekslingsstudenter (

Recommended Previous Knowledge
MAT121 Linear Algebra, STAT101 Elementary Statistics or STAT110 Basic Course in Statistics, and STAT210 Theory of Statistical Inference
Forms of Assessment
Oral examination
Grading Scale
The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.