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250078 VO Advanced probability theory (2013S)
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Details
Language: German
Examination dates
- Monday 01.07.2013
- Wednesday 10.07.2013
- Friday 12.07.2013
- Monday 15.07.2013
- Wednesday 18.12.2013
- Tuesday 01.04.2014
- Wednesday 07.05.2014
- Tuesday 17.06.2014
- Tuesday 18.11.2014
- Wednesday 18.02.2015
- Thursday 02.07.2015
Lecturers
Classes (iCal) - next class is marked with N
- Monday 04.03. 13:15 - 15:00 Seminarraum
- Thursday 07.03. 11:15 - 13:00 Seminarraum
- Thursday 14.03. 11:15 - 13:00 Seminarraum
- Monday 18.03. 13:15 - 15:00 Seminarraum
- Thursday 21.03. 11:15 - 13:00 Seminarraum
- Monday 08.04. 13:15 - 15:00 Seminarraum
- Thursday 11.04. 11:15 - 13:00 Seminarraum
- Monday 15.04. 13:15 - 15:00 Seminarraum
- Thursday 18.04. 11:15 - 13:00 Seminarraum
- Monday 22.04. 13:15 - 15:00 Seminarraum
- Thursday 25.04. 11:15 - 13:00 Seminarraum
- Monday 29.04. 13:15 - 15:00 Seminarraum
- Thursday 02.05. 11:15 - 13:00 Seminarraum
- Monday 06.05. 13:15 - 15:00 Seminarraum
- Monday 13.05. 13:15 - 15:00 Seminarraum
- Thursday 16.05. 11:15 - 13:00 Seminarraum
- Thursday 23.05. 11:15 - 13:00 Seminarraum
- Monday 27.05. 13:15 - 15:00 Seminarraum
- Monday 03.06. 13:15 - 15:00 Seminarraum
- Thursday 06.06. 11:15 - 13:00 Seminarraum
- Monday 10.06. 13:15 - 15:00 Seminarraum
- Thursday 13.06. 11:15 - 13:00 Seminarraum
- Monday 17.06. 13:15 - 15:00 Seminarraum
- Thursday 20.06. 11:15 - 13:00 Seminarraum
- Monday 24.06. 13:15 - 15:00 Seminarraum
- Thursday 27.06. 11:15 - 13:00 Seminarraum
Information
Aims, contents and method of the course
Assessment and permitted materials
oral exam
Minimum requirements and assessment criteria
understanding the theory
Examination topics
lectures
Reading list
will be announced during the lectures
Association in the course directory
MSTW
Last modified: Mo 07.09.2020 15:40
formalised and analysed once measure theory is available. The lectures
offer an introduction to this "advanced" theory. We shall discuss the
existence of suitable models, and the most important limit theorems for
sequences of random variables, like the law of large numbers (and, more
generally, the ergodic theorem), the central limit theorem and extensions
(e.g. to function spaces), and study some important types of stochastic
processes (including Brownian motion).