Special Methods for Data Analysis
Integrated course, 5.00 ECTS
Course content
The course introduces multivariate statistical methods in detail. These include topics such as correlation and covariance, partial least squares, PC analysis, discriminant analysis, factor analysis, Markov chains and their application, maximum likelihood methods and Bayesian statistics.
Learning outcomes
The graduate gains mathematical-statistical skills that are required for practical data analysis.
Recommended or required reading and other learning resources / tools
Books: Simon Munzert: Automated Data Collection with R; Udo Kuckartz, Statistik; Andy Field: Discovering Statistics Using SPSS; Wolf-Michael Kähler: Statistische Datenanalyse
Journals:
Mode of delivery
2 THW Lecture, 1 THW Tutorial
Prerequisites and co-requisites
Module MAT 1
Assessment methods and criteria
Lecture: final exam, Tutorial: continuous appraisal