Universität Wien

040038 VO Econometrics and Statistics (MA) (2024S)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
ON-SITE
Moodle
We 08.05. 16:45-18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
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Details

Language: German

Examination dates

Wednesday 25.09.2024 16:45 - 18:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock

Lecturers

Classes (iCal) - next class is marked with N

Wednesday 06.03. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday 13.03. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday 20.03. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday 10.04. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday 17.04. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday 24.04. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday 15.05. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday 22.05. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday 29.05. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday 05.06. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday 12.06. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday 19.06. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday 26.06. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß

Information

Aims, contents and method of the course

Datamining and big data based on case studies

During the course we will learn and discuss concepts of data mining and big data using case studies.
The case studies will cover areas such as

. Customer Relationship Management
. Fraud Detection
. Revenue Management
. Market Research

The presented concepts of data-naming and big data will include i.a.

. Multiple Regression,
. Logistic Regression
. Statistical Analysis of Frequency Data
. Analysis of variance
. Time series analysis
. Supervised und unsupervised learning

Assessment and permitted materials

Written Exam

Minimum requirements and assessment criteria

To pass this course you have to attain min 60% of the total points.

Examination topics

Analyze a given Problem and sketch a solution with Datamining methods

Understand (= be able to read and Interpret) statistical model equations
and Datamining concepts

More Details about the exam will be given during the course.

Reading list

Folien und Audio
Themenbezogen Literaturhinweise während des Kurses

Association in the course directory

Last modified: We 06.03.2024 10:45