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#70190 / #4

Seit WS 2019/20


Multivariate Analysis/Business Statistics


Werwatz, Axel


Schriftliche Prüfung


Fakultät VII

Institut für Volkswirtschaftslehre und Wirtschaftsrecht

37312100 FG Ökonometrie und Wirtschaftsstatistik



H 57

Plitzko, Franziska


Learning Outcomes

How to use statictical methods to explore, summarize, classify, cluster or explain multivariate data.


Explorative data analysis, Multivariate Distributions and Inference, Discriminant Analysis, Cluster Analysis, Principal Component Analysis, Factor Analysis

Module Components


All Courses are mandatory.

Course NameTypeNumberCycleLanguageSWSVZ
Multivariate Analysis/Business StatisticsVL71 210 L 1586SoSeEnglish2
Multivariate Analysis/Business StatisticsUE71 210 L 1587SoSeEnglish2

Workload and Credit Points

Multivariate Analysis/Business Statistics (VL):

Workload descriptionMultiplierHoursTotal
60.0h(~2 LP)
Class attendance15.02.0h30.0h
Pre/post processing15.02.0h30.0h

Multivariate Analysis/Business Statistics (UE):

Workload descriptionMultiplierHoursTotal
60.0h(~2 LP)
Class attendance15.02.0h30.0h
Pre/post processing15.02.0h30.0h

Course-independent workload:

Workload descriptionMultiplierHoursTotal
60.0h(~2 LP)
Exam preparation1.060.0h60.0h
The Workload of the module sums up to 180.0 Hours. Therefore the module contains 6 Credits.

Description of Teaching and Learning Methods

Lecture and Exercise. Exercises take place at the computer lab where real or simulated data and the statistics software package STATA is used. An introduction to STATA will be given at the beginning of the course (Übung/Exercises).

Requirements for participation and examination

Desirable prerequisites for participation in the courses:


Mandatory requirements for the module test application:

1. Requirement
Modul70232 [Statistik II für Wirtschaftswissenschaften] passed
2. Requirement
Modul70231 [Statistik I für Wirtschaftswissenschaften] passed

Module completion



Type of exam

Written exam




Exam will take 90min

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
1 Semester.

This module may be commenced in the following semesters:

Maximum Number of Participants

This module is not limited to a number of students.

Registration Procedures

Please note the information posted on the website (http://www.statistik.tu-berlin.de).

Recommended reading, Lecture notes

Lecture notes

Availability:  unavailable


Electronical lecture notes

Availability:  available
Additional information:
Unterlage wird passwortgeschützt für Teilnehmer auf ISIS hochgeladen.



Recommended literature
Afifi, A., Clark, V. A. und May, S. (2004), Computer-Aided Multivariate Analysis, 4th Edition, Chapman & Hall
Backhaus, K., Erichson, B. und Plinke, W. (2006), Multivariate Analysemethoden - Eine anwendungsorientierte Einführung, 11. Aufl., Springer Verlag
Hamilton, L. C. (2006), Statistics with STATA, Brooks/Cole
Härdle, W. und Simar, L. (2006), Applied Multivariate Statistical Analysis, Springer
Hastie, T., Tibshirani, R. und Friedman, J. H. (2003) The Elements of Statistical Learning, Springer

Assigned Degree Programs

This module is used in the following Degree Programs (new System):

Studiengang / StuPOStuPOsVerwendungenErste VerwendungLetzte Verwendung
Industrial Economics (M. Sc.)18WS 2019/20SoSe 2023
Information Systems Management (Wirtschaftsinformatik) (M. Sc.)212WS 2019/20SoSe 2023
Soziologie technikwissenschaftlicher Richtung (B. A.)18WS 2019/20SoSe 2023
Wirtschaftsingenieurwesen (M. Sc.)19WS 2019/20SoSe 2023

Students of other degrees can participate in this module without capacity testing.


No information