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First lecture: Thursday, Sep. 17.
First exercise class: Tuesday, Sep. 22.
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 | Mayra Bermúdez C. | Exercise classes | Tue 13-14 |
HG E 33.1 HG F 26.5 |
ML H 34.3 ML J 37.1 |
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.
An electronic version of the lecture notes will be available for registered students. A printed version will be available for purchase (CHF 15) at the end of the first lecture as well as during "Präsenz".
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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