Multivariate Methods - Prof. Dr. Uwe Jensen

Deckblatt Multi_Methods


I. Syllabus:

Many textbooks are either too technical (concentrating on the derivation of techniques) or too applied (following the cookbook approach). In this course, students will get an introduction to the various multivariate techniques with an emphasis on geometrical intuition and understanding. The techniques will be applied to data from the German Socioeconomic Panel (GSOEP). Software: Stata

  • Analysis of Variance
  • Eigenvalues
  • Principal Components Analysis
  • Factor Analysis
  • Canonical Correlation Analysis
  • Discriminant Analysis
  • Cluster Analysis
  • Multidimensional Scaling
  • Correspondence Analysis


II. Prerequisites:

  • Introductory Statistics
  • Linear Algebra
  • Matrix Algebra
  • Introductory Econometrics


III. Downloads:


IV. Literature:

  • Cox, T.F.: An introduction to multivariate data analysis. Hodder Arnold (London)
  • Fahrmeir, L., A. Hamerle, G. Tutz: Multivariate statistische Verfahren. De Gruyter (Berlin)
  • Sharma, S.: Applied Multivariate techniques. Wiley (New York)