Universität Wien

040195 KU Data Analysis on Organization and Personnel (MA) (2024W)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Prüfungsimmanente Lehrveranstaltung

service email address: opim.bda@univie.ac.at
Moodle

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 24 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Donnerstag 03.10. 09:45 - 14:45 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Freitag 04.10. 09:45 - 14:45 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Donnerstag 31.10. 09:45 - 14:40 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Dienstag 05.11. 09:45 - 14:45 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Freitag 24.01. 14:15 - 15:45 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

Summary: This course introduces students to multivariate statistics for analyzing data in human resources, economics, and related disciplines.
The aim of this course is to provide participants with an understanding of the quantitative research process from hypotheses development to testing the hypotheses with the appropriate statistical methods.

Goal: Upon completion of the course, participants should be able to conduct their own study and analyses data sets with a variety of statistical methods. Discussed topics include:

• Developing and testing hypotheses
• Introduction to univariate and multivariate methods
• Regression analysis

The emphasis is on empirical applications and the mathematics of econometric will be introduced only as needed.

Art der Leistungskontrolle und erlaubte Hilfsmittel

The final grade will be based on assignments, presentations, and active in class participation. Attendance during the lectures is mandatory.

The use of AI tools (e.g. ChatGPT) for the production of texts is not allowed.

Mindestanforderungen und Beurteilungsmaßstab

Basic knowledge of Business Mathematics and Statistics are required.
Passing grades can generally not be earned by students who miss more than 10% of the total class-time.
1 (sehr gut) → 100-89 poins
2 (gut) → 88-76 poins
3 (befriedigend) → 75-63 poins
4 (genügend) → 62-50 poins
5 (nicht genügend) → 49-0 poins

Prüfungsstoff

The final grade will be based on assignments, presentations, in class discussion and participation. Attendance during the lectures is mandatory.

The use of AI tools (e.g. ChatGPT) for the production of texts is not allowed.

Literatur

Wooldridge „Introductory Econometrics“
– Chapters 1-8, 15, 17
Peter Kennedy „A guide to Econometrics“
– Chapters 1-12, 16, 17
Kohler/Kreuter „Data Analysis using Stata“
– Chapter 8 and 9

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mo 24.03.2025 12:45