After successful completion of the course, students are able to operate elementary probability calculus, to generate discrete and continuous variables, to estimate unknown parameters from random samples and to test hypotheses. Students learn to solve exercises with self-written program codes.

Elementary introduction to probability; Bayes' theorem; counting experimants, discrete random variables; measurement experiments and continuous random variables; random samples and sample statistics; and their properties; moment estimators, maximum likelihood estimators, bayes estimators; confidence intervals and credible intervals; testing of hypotheses; linear models and regression.

Derivation of algorithms, graphical representations, solving examples 

The course starts on October  2020, and ends December 2020. 

The slides can be downloaded at http://www.hephy.at/user/wwaltenberger/stat2020/Folien.pdf

 The lectures will be held via a YouTube channel with live-chat, and debriefings on zoom.

During a written exam the lecture subjects are tested by open questions. Exam duration: 120 minutes.

The course is based on the book "Wahrscheinlichkeitsrechnung und Statistik für Studierende der Physik" which can be downloaded from:

http://bookboon.com/de/wahrscheinlichkeitsrechnung-und-statistik-ebook

In addition:

Sheldon M. Ross, Introduction to Probability and Statistics for Engineers and Scientists, Academic Press

Mathematics of the first two semesters