In this course, students familiarize themselves with a range of statistical techniques used for analyzing multivariate data structures. Topics include:
- multivariate distributions (properties, multivariate normal, multivariate t, Wishart)
- more flexible techniques for multivariate data: mixture models & copulae
- factor models (dimension reduction techniques): principal components analysis, factor analysis
- classification techniques: clustering.

Next to developing a thorough understanding of the concepts and statistical properties of the different techniques, students also apply their knowledge on real data in small teams and individually and report about their findings in an academically professional way.

Vrije Universiteit Amsterdam (VU Amsterdam) awards credits based on the ECTS system. Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA?s recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.