142.340 Statistical methods in data analysis
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2022W, SV, 2.0h, 3.0EC

Course evaluation

Properties

  • Semester hours: 2.0
  • Credits: 3.0
  • Type: SV Special Lecture
  • Format: Presence

Learning outcomes

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.

 

 

 

 

 

 

 

 

 

 

 

 

Subject of course

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.

 

 

 

 

 

 

 

 

 

 

 

 

Teaching methods

Derivation of algorithms, graphical representations, solving examples 

 

 

 

 

 

 

 

 

 

 

 

 

Mode of examination

Written

Additional information

The course starts October 14th 2022, and ends December 2022. 

Briefing takes place october 4th, 2:00 pm on zoom.

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

 

 

 

 

 

 

 

 

 

 

 

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Tue14:00 - 15:0004.10.2022 https://oeaw-ac-at.zoom.us/my/walten?pwd=STUzalYySTJYWlh4MzZlUmFwcG1mZz09 (LIVE)briefing, virtually via zoom https://oeaw-ac-at.zoom.us/my/walten?pwd=STUzalYySTJYWlh4MzZlUmFwcG1mZz09
Fri10:30 - 13:0014.10.2022 - 21.10.2022 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 WienLecture
Fri10:30 - 11:3028.10.2022 - 20.01.2023 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 WienLecture
Statistical methods in data analysis - Single appointments
DayDateTimeLocationDescription
Tue04.10.202214:00 - 15:00 https://oeaw-ac-at.zoom.us/my/walten?pwd=STUzalYySTJYWlh4MzZlUmFwcG1mZz09briefing, virtually via zoom https://oeaw-ac-at.zoom.us/my/walten?pwd=STUzalYySTJYWlh4MzZlUmFwcG1mZz09
Fri14.10.202210:30 - 13:00 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 WienLecture
Fri21.10.202210:30 - 13:00 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 WienLecture
Fri28.10.202210:30 - 11:30 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 WienLecture
Fri04.11.202210:30 - 11:30 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 WienLecture
Fri11.11.202210:30 - 11:30 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 WienLecture
Fri18.11.202210:30 - 11:30 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 WienLecture
Fri25.11.202210:30 - 11:30 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 WienLecture
Fri02.12.202210:30 - 11:30 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 WienLecture
Fri09.12.202210:30 - 11:30 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 WienLecture
Fri16.12.202210:30 - 11:30 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 WienLecture
Fri13.01.202310:30 - 11:30 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 WienLecture
Fri20.01.202310:30 - 11:30 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 WienLecture

Examination modalities

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

 

 

 

 

 

 

 

 

 

 

 

 

Course registration

Begin End Deregistration end
05.09.2022 00:00 02.10.2022 23:59 04.10.2022 13:00

Registration modalities

 

 
 
 
 
 

Curricula

Literature

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


 

Previous knowledge

Mathematics of the first two semesters

 

 

 

 

 

 

 

 

 

 

 

 

Accompanying courses

Language

German