After completing the course the student is expected to - know and be able to use multivariate statistical methods - know to the underlying theory of multivariate statistical methods
Multivariate data; Basic measures and statistics Inference for one- and two-means; Profile analysis; Multiple comparisons Multivariate general linear model: MANOVA and Multivariate regression Principal components analysis Canonical correlation analysis Discriminant analysis
Teaching can be given in the form of lectures, calculation exercises and computer exercises.
The examination takes place partly through a written examination at the end of the course and/or through presentation orally and in written form of compulsory assignments.
The course is included in the Master's programme in statistics.