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University of Oldenburg
28.05.2022 02:48:28
wir808 - Multivariate Statistics (Complete module description)
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Module label Multivariate Statistics
Module code wir808
Credit points 6.0 KP
Workload 180 h
Institute directory Department of Business Administration, Economics and Law (Business Administration and Business Education)
Applicability of the module
  • Master's Programme Business Administration, Economics and Law (Master) > Basismodule
  • Master's Programme Business Administration, Economics and Law (Master) > Mantelmodule (MPO2020)
  • Master's Programme Business Administration, Economics and Law (Master) > Schwerpunkt "Volkswirtschaftslehre" (VWL) (MPO2020)
  • Master's Programme Business Informatics (Master) > Module der Wirtschafts- und Rechtswissenschaften (Master)
  • Master's Programme Computing Science (Master) > Nicht Informatik
  • Master's Programme Environmental Modelling (Master) > Mastermodule
  • Master's Programme Sustainability Economics and Management (Master) > Basic and Accentuation Modules
Responsible persons
Stecking, Ralf Werner (Module responsibility)
Lehrenden, Die im Modul (Authorized examiners)
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.
Reader's advisory
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
Language of instruction German
Duration (semesters) 1 Semester
Module frequency jährlich
Module capacity unlimited
Modullevel / module level MM-PB (Professionalisierungsbereichsmodul im Master)
Modulart / typ of module je nach Studiengang Pflicht oder Wahlpflicht
Lehr-/Lernform / Teaching/Learning method
Vorkenntnisse / Previous knowledge
Course type Comment SWS Frequency Workload of compulsory attendance
2 28
2 28
Total time of attendance for the module 56 h
Examination Time of examination Type of examination
Final exam of module
at the end of the semester
written exam or oral exam