Stud.IP Uni Oldenburg
University of Oldenburg
21.10.2019 23:10:18
wir808 - Multivariate Statistics
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Module label Multivariate Statistics
Module code wir808
Credit points 6.0 KP
Workload 180 h
Faculty/Institute Department of Business Administration, Economics and Law (Business Administration and Business Education)
Used in course of study
  • Master's Programme Business Administration, Economics and Law (Master) >
  • Master's Programme Business Administration, Economics and Law (Master) >
  • Master's Programme Business Informatics (Master) >
  • Master's Programme Environmental Modelling (Master) >
  • Master's Programme Sustainability Economics and Management (Master) > Additional Modules
Contact person
Module responsibility
Authorized examiners
Entry requirements
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
Links
Language of instruction German
Duration (semesters) 1 Semester
Module frequency jährlich
Module capacity unlimited
Modullevel MM-PB (Professionalisierungsbereichsmodul im Master)
Modulart je nach Studiengang Pflicht oder Wahlpflicht
Lern-/Lehrform / Type of program
Vorkenntnisse / Previous knowledge
Course type Comment SWS Frequency Workload attendance
Lecture 2.00 28 h
Exercises 2.00 28 h
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

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