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401-0601-00L 5 Credits

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Probability and Statistics

Wahrscheinlichkeit und Statistik

Lecturers & Examiners: Prof. Dr. Martin Schweizer

VVZ CR n/a

Last Updated: 2026-02-05 14:59:56

Abstract

Basic concepts from probability theory and statistics:- descriptive statistics (including graphical methods)- introduction to probability theory- introduction to basic concepts and methods from analytic statistics

Objective

a) the ability to understand the covered methods from probability theory and to apply them in other contexts b) the ability to perform basic statistical tests and to interpret the results

Content

Basic concepts from probability theory and statistics which are needed by students of computer science in the course of their studies The conceptual goals are - learning from data - the laws of randomness and probabilistic thinking (thinking in probabilities) - simple and basic methods from analytic (deductive) statistics The contents of the course encompasses - descriptive statistics (including graphical methods) - an introduction to probability theory: basic concepts (probability space, probability measure), independence, random variables, discrete and continuous distributions, multivariate distributions, conditional distributions, expectation and variance, limit theorems - methods from analytic statistics: parameter estimation, maximum likelihood and moment methods, tests (including t-test, F-test, chi-square-test), confidence intervals

Resources

Lecture Notes

Details will be announced in the course.

Literature