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Probability Theory
Wahrscheinlichkeitstheorie
Last Updated: 2026-02-05 15:05:36
Abstract
Basics of probability theory and the theory of stochastic processes in discrete time
Objective
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 - Probability measures on product spaces (stochastic kernels, Ionescu-Tulcea theorem) - Conditional expectations - Martingales (stopping times, stopping theorem, convergence theorems, applications) - Weak convergence (Prohorov's theorem, characteristic functions) - perhaps Brownian motion and Donsker's theorem
Content
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 - Probability measures on product spaces (stochastic kernels, Ionescu-Tulcea theorem) - Conditional expectations - Martingales (stopping times, stopping theorem, convergence theorems, applications) - Weak convergence (Prohorov's theorem, characteristic functions) - perhaps Brownian motion and Donsker's theorem
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 |