Universität Wien

040129 VO Statistics 1 (2017S)

6.00 ECTS (3.00 SWS), SPL 4 - Wirtschaftswissenschaften

Ausführliche Kursbeschreibung und Informationen zu Fragestunden und Tutorien auf Homepage

http://homepage.univie.ac.at/erhard.reschenhofer/

Fragestunde (Thomas Stark): DI wtl von 07.03.2017 bis 27.06.2017 16.45-18.15 Ort: Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock

Tutorium (Jan-Michael van Linthoudt): MI wtl von 01.03.2017 bis 10.05.2017 08.00-09.30 Ort: Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Am MI 22.03.2017 findet kein Tutorium statt.

Fragestunde (Manveer Mangat): FR wtl von 10.03.2017 bis 30.06.2017 11.30-13.00 Ort: Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock

Details

Language: German

Examination dates

Lecturers

Classes (iCal) - next class is marked with N

See: http://homepage.univie.ac.at/erhard.reschenhofer/

Tuesday 07.03. 11:30 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday 09.03. 08:00 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Tuesday 14.03. 11:30 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday 16.03. 08:00 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Tuesday 21.03. 11:30 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday 23.03. 08:00 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Tuesday 28.03. 11:30 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday 30.03. 08:00 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Tuesday 04.04. 11:30 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday 06.04. 08:00 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Tuesday 25.04. 11:30 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday 27.04. 08:00 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß

Information

Aims, contents and method of the course

Objective:
To introduce students to statistics

Topics include:
Logic and set theory, events and their probabilities, discrete random variables, continuous random variables, Central Limit Theorem, estimation, testing, linear regression, statistical software R

On successful completion of the course, students should be able to:
Calculate probabilities and conditional probabilities, work with random variables and distribution functions, apply the Central Limit Theorem, find the bias and mean square error of estimators, test statistical hypotheses, analyze data using linear models, display data using graphical methods

Teaching and learning methods:
Lectures

Assessment and permitted materials

Written exam (no aids are permitted)

Minimum requirements and assessment criteria

Eight of the fifteen questions must be answered correctly to pass the exam.

Examination topics

Lecture notes on homepage

Reading list

R. J. Larsen and M. L. Marx: Introduction to Mathematical Statistics and its Applications. Pearson Prentice Hall

Association in the course directory

Last modified: Mo 07.09.2020 15:28