Multivariate Statistical Analysis (WiSe 24/25)

Content of this course:

This course gives a detailed treatment of different multivariate statistical analysis techniques commonly used as well as the statistical framework underpinning these methods. Students will advance their ability to discuss and apply multivariate data analysis techniques in practice.

This course begins with some data visualizations  for multivariate data and a short recapitulation of matrix algebra.  Then, multivariate distributions (in particuluar, the normal and related distributions) and their properties as well as  estimation and testing in the multivariate case are presented.  Finally, different supervised and unsupervised multivariate techniques including cluster analysis, discriminant analysis, principal component analysis, factor analysis, multidimensional scaling, canonical correlation and graphical models are discussed.

Data protection and copyright:

Some lecture and exercise classes might be conducted online via Zoom video conferences.  It is prohibited to record these video conferences in any way (video, audio, screenshots, etc.). The content of the course, including all provided material, is intellectual property of the respective lecturer (unless declared otherwise) and protected by copyright. Only students enrolled in this Moodle course are allowed to use it. In particular, the publication (also partial), duplication, dissemination, and editing of our material (including video conferences) are prohibited. Any violation can be prosecuted.

All students enrolled in the Moodle course pledge themselves to observe the data protection and copyright rules and to use the material (including video conferences) only in the context of their studies individually.

By enrolling in this Moodle course, you agree to these data protection and copyright rules.