Universität Wien

250100 VO Advanced probability theory (2016S)

7.00 ECTS (4.00 SWS), SPL 25 - Mathematik

Details

Language: German

Examination dates

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 02.03. 11:30 - 13:00 Seminarraum 8 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 07.03. 11:30 - 13:00 Seminarraum 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 09.03. 11:30 - 13:00 Seminarraum 8 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 14.03. 11:30 - 13:00 Seminarraum 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 16.03. 11:30 - 13:00 Seminarraum 8 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 04.04. 11:30 - 13:00 Seminarraum 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 06.04. 11:30 - 13:00 Seminarraum 8 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 11.04. 11:30 - 13:00 Seminarraum 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 13.04. 11:30 - 13:00 Seminarraum 8 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 18.04. 11:30 - 13:00 Seminarraum 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 20.04. 11:30 - 13:00 Seminarraum 8 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 25.04. 11:30 - 13:00 Seminarraum 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 27.04. 11:30 - 13:00 Seminarraum 8 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 02.05. 11:30 - 13:00 Seminarraum 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 04.05. 11:30 - 13:00 Seminarraum 8 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 09.05. 11:30 - 13:00 Seminarraum 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 11.05. 11:30 - 13:00 Seminarraum 8 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 18.05. 11:30 - 13:00 Seminarraum 8 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 23.05. 11:30 - 13:00 Seminarraum 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 25.05. 11:30 - 13:00 Seminarraum 8 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 30.05. 11:30 - 13:00 Seminarraum 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 01.06. 11:30 - 13:00 Seminarraum 8 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 06.06. 11:30 - 13:00 Seminarraum 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 08.06. 11:30 - 13:00 Seminarraum 8 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 13.06. 11:30 - 13:00 Seminarraum 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 15.06. 11:30 - 13:00 Seminarraum 8 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 20.06. 11:30 - 13:00 Seminarraum 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 22.06. 11:30 - 13:00 Seminarraum 8 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 27.06. 11:30 - 13:00 Seminarraum 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 29.06. 11:30 - 13:00 Seminarraum 8 Oskar-Morgenstern-Platz 1 2.Stock

Information

Aims, contents and method of the course

The lecture presents the most important results and concepts of the modern probability theory, using the measure-theoretic framework, in the context of infinite sequences of random variables, i.e. stochastic processes in discrete time. It gives an introduction to basic convergence results for such sequences:
- laws of large numbers, central limit theorem, large deviation for independent sequences
- convergence of stochastic series
- martingale convergence theorems
- convergence of Markov chains
It further discusses the theory of the weak convergence of probability measures on function spaces, aiming on a rigorous construction of the Brownian motion via Donsker's theorem.

Assessment and permitted materials

Oral exam, approx. 30 min.

Minimum requirements and assessment criteria

Knowledge and understanding of the lecture content

Examination topics

Reading list

see http://www.mat.univie.ac.at/~cerny/teaching-SS2016.html

Association in the course directory

MSTW

Last modified: Mo 07.09.2020 15:40