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040038 VO Econometrics and Statistics (MA) (2020S)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften

Moodle

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).

Details

Language: German

Examination dates

Lecturers

Bertram Wassermann

Classes (iCal) - next class is marked with N

Instructions will be sent by per E-Mail.

All kinds of questions send to
Bertram.wassermann@univie.ac.at

Material can be downloaded from
https://homepage.univie.ac.at/bertram.wassermann/SS20/WS20index.html

Tuesday 03.03. 16:45 - 18:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday 10.03. 16:45 - 18:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday 31.03. 16:45 - 18:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday 21.04. 16:45 - 18:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday 28.04. 16:45 - 18:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday 05.05. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Tuesday 12.05. 16:45 - 18:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday 19.05. 16:45 - 18:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday 26.05. 16:45 - 18:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday 09.06. 16:45 - 18:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday 16.06. 16:45 - 18:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday 23.06. 16:45 - 18:15 Hörsaal 3 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.

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

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 die im Kurs diskutiert werden .

Association in the course directory

Last modified: Fr 12.05.2023 00:12