Universität Wien

250068 VO Stochastic processes (2023W)

5.00 ECTS (3.00 SWS), SPL 25 - Mathematik
ON-SITE
Moodle

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Details

Language: English

Examination dates

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 04.10. 16:45 - 18:15 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Friday 06.10. 11:30 - 13:00 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 11.10. 16:45 - 18:15 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 18.10. 16:45 - 18:15 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Friday 20.10. 11:30 - 13:00 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 25.10. 16:45 - 18:15 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Friday 03.11. 11:30 - 13:00 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 08.11. 16:45 - 18:15 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 15.11. 16:45 - 18:15 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Friday 17.11. 11:30 - 13:00 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 22.11. 16:45 - 18:15 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 29.11. 16:45 - 18:15 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Friday 01.12. 11:30 - 13:00 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 06.12. 16:45 - 18:15 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 13.12. 16:45 - 18:15 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Friday 15.12. 11:30 - 13:00 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 10.01. 16:45 - 18:15 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 17.01. 16:45 - 18:15 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Friday 19.01. 11:30 - 13:00 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 24.01. 16:45 - 18:15 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 31.01. 16:45 - 18:15 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß

Information

Aims, contents and method of the course

This course offers an introduction to the theory of random processes, focusing on important basic classes of examples (Markov chains in discrete and continuous time, random walks, branching processes, Poisson processes). Prerequisites are a good understanding of probability theory, analysis and linear algebra.

Assessment and permitted materials

exam

Minimum requirements and assessment criteria

understanding and ability to explain and apply the theory

Examination topics

Good understanding and working knowledge of the topics discussed in the lecture course.

Reading list

Will be specified during the lectures.

Association in the course directory

MBIP; MSTP

Last modified: Fr 30.08.2024 12:26