wir808 Multivariate Statistics (Complete module description)

Module label	Multivariate Statistics
Modulkürzel	wir808
Credit points	6.0 KP
Workload	180 h
Verwendbarkeit des Moduls	Master's Programme Business Administration, Economics and Law > Basismodule Master's Programme Business Administration, Economics and Law > Mantelmodule (MPO2020) Master's Programme Business Administration, Economics and Law > Schwerpunkt "Volkswirtschaftslehre" (VWL) (MPO2020) Master's programme Business Administration: Management and Law > Basismodule Master's Programme Business Informatics > Business Informatics more... Master's Programme Business Informatics > Module der Wirtschafts- und Rechtswissenschaften (Master) Master's Programme Computing Science > Module aus anderen Studiengängen Master's Programme Environmental Modelling > Mastermodule Master's Programme Sustainability Economics and Management > Basic Modules Master's Programme Sustainability Economics and Management > Basic Modules
Zuständige Personen	Stecking, Ralf Werner (module responsibility) Lehrenden, Die im Modul (Prüfungsberechtigt)
Prerequisites
Skills to be acquired in this module	With successful completion of the course, students shall: be aware of and be able to evaluate advanced methods of multivariate data analysis. be able to select adequate methods in relevant fields of application, like prediction, classification, and segmentation analysis. be able to run computer-aided analyses and to interpret the results properly.
Module contents	Various methods of quantitative data analysis such as: Linear Regression, Logistic Regression, Linear Discriminant Analysis, Principal Component Analysis, Feature selection and evaluation methods.
Literaturempfehlungen	Backhaus, Erichson, Plinke, Weiber (2015): Multivariate Analysemethoden, 14. Aufl., Springer, Berlin Litz, H.P. (2000): Multivariate Statistische Methoden, Oldenbourg, München Hartung, J. und Elpelt, B. (2006): Multivariate Statistik, 7. Aufl., Oldenbourg, München Berthold, M. und Hand, D.J. (2010): Intelligent Data Analysis, 2. Aufl., Springer, Berlin Witten, I.H. und Frank, E. (2011): Data Mining, 3. Aufl., Morgan Kaufmann, San Francisco
Links
Language of instruction	German
Duration (semesters)	1 Semester
Module frequency	jährlich
Module capacity	unrestricted
Type of module	je nach Studiengang Pflicht oder Wahlpflicht
Module level	MM-PB (Professionalisierungsbereichsmodul im Master)

Lehrveranstaltungsform	SWS	Contact-time workload
Lecture	2	28
Exercises	2	28
Präsenzzeit Modul insgesamt		56 h

Examination	Prüfungszeiten	Type of examination
Final exam of module	at the end of the semester	written exam or oral exam