Department of Mathematics

Probability Theory

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First lecture: Tuesday, Sep. 16.
First exercise class: Tuesday, Sep. 23 or Wednesday, Sep. 24.

Exercise classes: Information about exercises can be found here.

Question times ("Präsenz"): Mondays and Thursdays, 12:00 – 13:00, in HG G 32.6.

Lecturer Prof. Alain-Sol Sznitman Lectures
Tue 10-12
Thu 10-12
HG G 3
Coordinator Xinyi Li 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 are planned:
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".

Additional literature

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

* These books are available as "Präsenzexemplare" in the mathematics library (HG G 7).
† The appendix (resp. Chapter 1 in the online version) contains a summary of measure theory.


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© 2016 Mathematics Department | Imprint | Disclaimer | 2 September 2015