Universität Wien

040771 UK Case Studies in Statistics (MA) (2025W)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
Moodle
We 12.11. 18:30-20:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 30 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 01.10. 18:30 - 20:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Wednesday 08.10. 18:30 - 20:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Wednesday 15.10. 18:30 - 20:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Wednesday 22.10. 18:30 - 20:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Wednesday 29.10. 18:30 - 20:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Wednesday 05.11. 18:30 - 20:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Wednesday 19.11. 18:30 - 20:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Wednesday 26.11. 18:30 - 20:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Wednesday 03.12. 18:30 - 20:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Wednesday 10.12. 18:30 - 20:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Wednesday 17.12. 18:30 - 20:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Wednesday 07.01. 18:30 - 20:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Wednesday 14.01. 18:30 - 20:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Wednesday 21.01. 18:30 - 20:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
  • Wednesday 28.01. 18:30 - 20:00 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock

Information

Aims, contents and method of the course

How does statistical data analysis look like in practice?

This question is investigated using case studies. We will examine the following topics:

Corporate Reporting
Revenue Management
Marketing
White-collar crime (fraud detection)

If necessary, a theoretical introduction will be given.

On the basis of data, most of which comes from practice, analyzes are designed, carried out, reports created and the results discussed together.

You should be familiar with the various forms of regression and the use of analysis software such as R, SPSS, SAS or similar. You should have access to your favorite Analysis Software.

Assessment and permitted materials

Project 1: A joint analysis project. On the basis of a data set, we go through an analysis process (almost) from the beginning to the final report.

Project 2: Students work out a topic individally and present the result to the group. Topics and relevant data are available.

Precence and Participation in the presentations of the others (Questions and Discussion)

Minimum requirements and assessment criteria

40% Project 1 and therefore presence
40% Project 2 and therefore presence
20% Participation

To be positive >= 60%

Examination topics

2 Projects and Discussion

Reading list

Folien
Weiterführende Literatur wird während der LV bekannt gegeben.

Association in the course directory

Last modified: We 24.09.2025 19:05