Universität Wien
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040129 VO Statistics 1 (2019S)

6.00 ECTS (3.00 SWS), SPL 4 - Wirtschaftswissenschaften

Ausführliche Kursbeschreibung auf Homepage

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

Fragestunde (Thomas Stark) findet statt: DI wtl von 05.03.2019 bis 25.06.2019 18.30-20.00 Ort: Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock; Die Fragestunden ab DI 07.05.2019 finden nur nach vorheriger E-Mail Anmeldung (thomas.stark@univie.ac.at) statt.

Fragestunde (Stefan Ortner) findet statt: MI wtl von 06.03.2019 bis 15.05.2019 und MI 29.05.2019, 19.06.2019 und 26.06.2019 09.45-11.15 Ort: Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock; DO 02.05.2019 09.45-11.15 Ort: Hörsaal 15 Oskar-Morgenstern-Platz 1 2.Stock; MI 22.05.2019, 05.06.2019 und 12.06.2019 09.45-11.15 Ort: Seminarraum 4 Oskar-Morgenstern-Platz 1 1.Stock; Die Fragestunden ab MI 08.05.2019 finden nur nach vorheriger E-Mail Anmeldung (stefan.ortner@univie.ac.at) statt.

Registration/Deregistration

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Details

Language: German

Examination dates

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 05.03. 11:30 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 07.03. 08:00 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 14.03. 08:00 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 19.03. 11:30 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 21.03. 08:00 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 26.03. 11:30 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 28.03. 08:00 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 02.04. 11:30 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 04.04. 08:00 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 09.04. 11:30 - 13:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 11.04. 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

More than 50% of the 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