Studies and Teaching

In close cooperation with the Chair of Statistics and Data Analytics, the Teaching Unit for Computational Statistics and Mathematics offers a wide range of courses in the fields of statistics and econometrics. In addition to basic methods of descriptive and inferential statistics, the main focus is on multivariate estimation and testing – especially in the context of regression analysis.

The core competence relevant for research and practice lies in the fact that methodological understanding is closely interlinked with the corresponding skills for the computer-aided implementation of statistical methods. Students are enabled to implement and interpret statistical procedures empirically and to evaluate corresponding analyses.

Important notes

There are no certificate exams (Scheinklausuren) offered in the field of statistics.
Students of Cultural Studies should contact the Chair of Methods of Empirical Social Research (Prof. Ingo Rohlfing, PhD) if they have any questions regarding classes in statistics or methodology (including the recognition of academic achievements at international faculties).
The courses "Computational Statistics - Regression in R" and "Computational Statistics - Statistical Learning in R" are open to students from other Master's programmes. After successfully passing the exam, they will receive a certificate of their acquired knowledge.

Mathematik für Wirtschaftswissenschaftler (Mathematics for economists, module no. 35400, held in German) [5 ECTS]: Students learn the basic mathematical skills required for business studies. By actively solving exercises and practical examples independently, you will learn how to transfer the techniques presented in the lecture to economic problems.
Statistik 1 und 2 für Wirtschaftswissenschaftler (Statistics 1 and 2 for economists, modules no. 35600a and 35600b, held in German) [10 ECTS]: Descriptive statistics and exploration of data; basics of probability calculation; random variables; discrete and continuous distributions; random samples; point and interval estimates; distribution-bound and distribution-free hypothesis tests; linear regression analysis; the use of standard statistical software.
Einführung in die Ökonometrie (Introduction to Econometrics, module no. 35555, held in German) [5 ECTS]: The central topic of the course is regression analysis, with which data-based economic relationships can be quantified and corresponding hypotheses tested. The degree of uncertainty underlying the results can be estimated.
Einführung in die Zeitreihenanalyse (Introduction to time series analysis, module no. 35560, held in German) [5 ECTS]: The module is designed as a basic event on the classical topics of time series analysis - such as level, trend, seasonal and cycle analysis. The first part of the module deals with intuitive, semi- and non-parametric methods, including the simple component model and various smoothing methods. The second part of the course introduces the theory, selection, estimation and diagnostics of ARIMA models. These still play a central role in the application of time series models in practice.
Computergestützte Statistik - Einführung in R (Computational Statistics - Introduction to R, module no. 35620, held in German) [3 ECTS]: The central topic is the introduction to the work with the statistics program R. In addition to teaching basic programming techniques (objects, functions, loops, etc..), this also includes an introduction to statistical data analysis (creating helpful tables and graphs, descriptive analyses, model estimates).