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Multivariate Statistics


  • The course is usually offered in winter semester.
  • In addition to the lecture exercises are offered where mathematical problems of the lecture are discussed and solved. It is suggested that students prepare the tasks beforehand.
  • Times of lectures and exercises can be found on KLIPS2.0

Content and Goals

Students acquire advanced knowledge of various multivariate techniques and gain experience in applying multivariate techniques in empirical economic research. They learn to understand and critically assess current contributions to research in multivariate statistics.

Contents of the module are: 

  • Multivariate distributions
  • Analysis of Variance
  • Eigenvalues
  • Principal Component Analysis
  • Factor Analysis
  • Discriminant Analysis
  • Cluster Analysis