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 Data might be outdated or incorrect.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 and Statistics
Wahrscheinlichkeitstheorie und Statistik
Last Updated: 2026-06-01 11:33:20
Abstract
Probability models and applications, introduction to statistical estimation and statistical tests
Objective
Ability to understand the covered methods and models from probability theory and to apply them in other contexts. Ability to perform basic statistical tests and to interpret the results
Content
The concept of probability space and some classical models: axioms of Kolmogorov, simple consequences, discrete models, densities, product spaces, relations between various models, distribution functions, transformations of probability distributions. Conditional probabilities, definition and examples, calculation of absolute probabilities from conditional probabilities, Bayes' formula, conditional distributions. Expectation of a random variable, application to coding, variance, covariance and correlation, linear predictions, law of large numbers, central limit theorem. Introduction to statistics: estimation of parameters and tests
Resources
Lecture Notes
yes
Literature
Textbuch: P. Brémaud: 'An Introduction to Probabilistic Modeling', Springer, 1988
Learning Materials (Links)
- Main link
- Information
General Information
- Language
- German
- Levels
- BSC
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- written 90 minutes
- Aids
- Hilfsmittel schriftlich: 5 A4-Blätter, beidseitig, von Hand beschrieben oder gedruckt (Schriftgrösse mindestens 11 Punkt), keine Taschenrechner.
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture | Wahrscheinlichkeitstheorie und Statistik |
|
2 h weekly |
| exercise |
Wahrscheinlichkeitstheorie und Statistik
Groups are selected in myStudies.
|
|
1 h weekly |