Universität Wien

040726 UK Mathematical Statistics (2023W)

10.00 ECTS (5.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
MIXED

Anwesenheit in erster Einheit unerlaesslich, da Warteliste gut gefuellt.
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. 65 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

MO, 29.01.24, 15 Uhr: Klausur!

  • Monday 02.10. 13:15 - 14:45 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 02.10. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 04.10. 13:15 - 16:30 Digital
  • Monday 09.10. 13:15 - 14:45 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 09.10. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 11.10. 13:15 - 16:30 Digital
  • Monday 16.10. 13:15 - 14:45 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 16.10. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 18.10. 13:15 - 16:30 Digital
  • Monday 23.10. 13:15 - 14:45 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 23.10. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 25.10. 13:15 - 16:30 Digital
  • Monday 30.10. 13:15 - 14:45 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 30.10. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 06.11. 13:15 - 14:45 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 06.11. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 08.11. 13:15 - 16:30 Digital
  • Monday 13.11. 13:15 - 14:45 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 13.11. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 15.11. 13:15 - 16:30 Digital
  • Monday 20.11. 13:15 - 14:45 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 20.11. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 22.11. 13:15 - 16:30 Digital
  • Monday 27.11. 13:15 - 14:45 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 27.11. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 29.11. 13:15 - 16:30 Digital
  • Monday 04.12. 13:15 - 14:45 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 04.12. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 06.12. 13:15 - 16:30 Digital
  • Monday 11.12. 13:15 - 14:45 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 11.12. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 13.12. 13:15 - 16:30 Digital
  • Monday 08.01. 13:15 - 14:45 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 08.01. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 10.01. 13:15 - 16:30 Digital
  • Monday 15.01. 13:15 - 14:45 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 15.01. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 17.01. 13:15 - 16:30 Digital
  • Monday 22.01. 13:15 - 14:45 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 22.01. 15:00 - 16:30 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 29.01. 15:00 - 16:30 Hörsaal 12 Oskar-Morgenstern-Platz 1 2.Stock
    Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock

Information

Aims, contents and method of the course

Basics of estimation and test theory, introduction to statistical modeling and decision theory.
Course is presented by streaming.

Assessment and permitted materials

Regular participation in the courses is desirable. At least 50% of the weekly exercises must be completed. Depending on the size of the group, you will present an exercise 2-3 times per semester in the course of the exercise. At the end of the semester, there is a written exam.

The use of AI tools (e.g. ChatGPT) for the production of texts is only permitted if they are expressly requested by the course leader (e.g. for individual work tasks).

Minimum requirements and assessment criteria

The grading will consist of the following points:
- Proportion of correctly solved exercises.
- Quality of the presented exercises.
- Result of the written exam.
The exact proportions and grading standards will be announced on Moodle and in the course of the first events.

Examination topics

content of the LV.

Reading list

There are many introductory statistics textbooks, e.g.
J. Lehn, H. Wegmann. Einführung in die Statistik.
H. Pruscha. Vorlesungen über Mathematische Statistik.
H. Pruscha. Angewandte Methoden der Mathematischen Statistik.
L. Breiman. Statistics: With a View Toward Applications.
V. Rohatgi. Statistical Inference.
G. Casella, R. L. Berger. Statistical Inference.
W. Pestman. Mathematical Statistics: An Introduction.
K. Bosch. Elementare Einführung in die angewandte Statistik: Mit Aufgaben und Lösungen.
The following textbooks cover both probability theory and statistics:
H. Dehling and B. Haupt. Einführung in die Wahrscheinlichkeitstheorie und Statistik.
U. Krengel. Einführung in die Wahrscheinlichkeitstheorie und Statistik.
H.O. Georgii. Stochastik: Einführung in die Wahrscheinlichkeitstheorie und Statistik.
The following books by Lehmann are classics:
E. L. Lehmann, G. Casella. Theory of Point Estimation.
E. L. Lehmann. Testing Statistical Hypotheses.
E. L. Lehmann. Elements of Large Sample Theory.
These two books are highly recommended because of their concentration on the essentials:
L. Wasserman. All of Statistics.
L. Wasserman. All of Nonparametric Statistics.

Association in the course directory

Last modified: Th 07.12.2023 13:45