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Probability Theory

Please note that this page is old.
Check in the VVZ for a current information.

First lecture: Tuesday 17/9/2013.

First exercise class: Tuesday 17/9/2013, Wednesday 18/9/2013 (1st week!)

Exercise classes: Information about the exercise classes can be found here.

Course Information: An information sheet about the course is available here (PDF).

Lecturer Prof. Pierre Nolin Lectures
Tue 10-12
Th 10-12
HG G 3
Coordinator Laurent Huber Exercise classes Tue 13-14 HG E 33.1
HG F 26.5
      Wed 9-10 HG F 26.3
HG F 26.5

Course contents

This course presents the basics of probability theory and the theory of stochastic processes in discrete time. The following topics will be covered in the course:
Basics in measure theory, random series, law of large numbers, weak convergence, characteristic functions, central limit theorem, conditional expectation, martingales, convergence theorems for martingales, Galton Watson chain, transition probability, Theorem of Ionescu Tulcea, Markov chains.

Lecture notes

Lecture notes will be available for purchase (15 CHF) at the end of the first lecture as well as during "Präsenz".

Examination

The course has a 30 minutes oral examination in English. The performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.

Additional literature

R. Durrett*, Probability: Theory and examples, Duxbury Press 1996
H. Bauer*, Wahrscheinlichkeitstheorie, 4. Auflage, de Gruyter Lehrbuch 1991
J. Jacod and P. Protter: Probability essentials, Springer 2004
D. Williams*, Probability with martingales, Cambridge University Press 1991
A. Klenke, Wahrscheinlichkeitstheorie, Springer 2008 (Online version)

* These books are available as "Präsenzexemplare" in the mathematics library (HG G 7).

 

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© 2016 Mathematics Department | Imprint | Disclaimer | 26 August 2014
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