VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.
Probability Theory
Wahrscheinlichkeitstheorie
Last Updated: 2026-02-05 15:14:48
Abstract
Basics of probability theory and the theory of stochastic processes in discrete time
Objective
Basic notions of probability theory and of stochastic processes in discrete time. Topics: summary of results in measure theory, random series, law of large numbers, weak convergence, characteristic functions, central limit theorem, conditional expectations, martingales, stopping times, convergence theorems, Galton Watson chain, probability kernels, theorem of Ionescu Tulcea, Markov chains.
Content
Basic notions of probability theory and of stochastic processes in discrete time. Topics: summary of results in measure theory, random series, law of large numbers, weak convergence, characteristic functions, central limit theorem, conditional expectations, martingales, stopping times, convergence theorems, Galton Watson chain, probability kernels, theorem of Ionescu Tulcea, Markov chains.
Resources
Lecture Notes
available, will be sold in the course
Literature
R. Durrett, Probability: Theory and examples, Duxbury Press 1996 J. Jacod and P. Protter, Probability essentials, Springer 2004 A. Klenke, Wahrscheinlichkeitstheorie, Springer 2006 J. Neveu, Bases mathematiques du calcul des probabilites, Masson 1980 D. Williams, Probability with martingales, Cambridge University Press 1991
General Information
- Language
- German
- Levels
- BSC , MSC
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- oral 30 minutes
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture | Wahrscheinlichkeitstheorie |
|
4 h weekly |
| exercise | Wahrscheinlichkeitstheorie |
|
1 h weekly |