Universität Wien

040771 UK Case Studies in Statistics (2021W)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
ON-SITE
Moodle

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 06.10. 16:45 - 18:15 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 13.10. 16:45 - 18:15 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 20.10. 16:45 - 18:15 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 27.10. 16:45 - 18:15 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 03.11. 16:45 - 18:15 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 10.11. 16:45 - 18:15 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 17.11. 16:45 - 18:15 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 24.11. 16:45 - 18:15 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 01.12. 16:45 - 18:15 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 15.12. 16:45 - 18:15 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 12.01. 16:45 - 18:15 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 12.01. 18:30 - 20:00 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 19.01. 16:45 - 18:15 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 19.01. 18:30 - 20:00 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 26.01. 16:45 - 18:15 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 26.01. 18:30 - 20:00 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.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.

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

Minimum requirements and assessment criteria

30% Project 1 and therefore presence
50% Project 2 and therefore presence
20% Participation

To be positive >= 60%

Examination topics

Reading list

Charts
Further literature will be announced during the course.

Association in the course directory

Last modified: Th 25.11.2021 09:48