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406-2604-AAL 7 Credits MSC D-MATH
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Probability and Statistics

Lecturers & Examiners: Prof. Dr. Fadoua Balabdaoui
Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement. Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.
VVZ CR n/a

Last Updated: 2026-02-05 16:06:47

Abstract

- Probability spaces- Discrete models, Randiom walk- Conditional probabilities, independence- Continuous models- Limit theorems==============================- Methods of moments- Maximum likelihood estimation- Hypothesis testing- Confidence intervals- Introductory Bayesian statistics- Linear regression model

Objective

The first part of the course gives an overview of the main concepts needed to understand probability theory (sample spaces, discrete models, random walk, contiuous models and limit theorems such as the Laws of Large Numbers and the Central limit theorem. Note that this part of the lectures will be given in German. The second part covers some fundamental results of mathematical statistics including estimation methods, hypothesis testing as well as the linear regression model. This part of the lectures will be offered in Englisch.

Resources

Lecture Notes

Wahrscheinlichkeitstheorie: basiert auf dem Skript "Wahrscheinlichkeitsrechnung und Statistik" von Prof. H. Foellmer und Prof. H. Kuensch (mit Ergaenzungen von Prof. J. Teichmann)Statistics: based on the script "Statistics for Mathematics" by Prof. S. van de Geer

Literature

A. DasGupta, Fundamentals of Probability: A First Course, Springer (2010) R. Berger and G. Casella, Statistical Inference, Duxbury Press (1990) J. A. Rice, Mathematical Statistics and Data Analysis, Wadsworth, second edition (1995)

General Information

Language
English
Levels
MSC
Frequency
Semesterly recurring

Examination

Type
session examination
Mode
written 180 minutes
Aids
Collection of formulas; precise format will be communicated in the course (Course 401-2604-00L Probability and Statistics (taught in the Spring Semester)) or on the course webpage.

Course Components

Type Title Time & Place Hours
revision course / private study Probability and Statistics
Self-study course. No presence required.
No time listed 210 h semesterly

Offered In