wir808 - Multivariate Statistics

wir808 - Multivariate Statistics

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Module label Multivariate Statistics
Modulkürzel wir808
Credit points 6.0 KP
Workload 180 h
Institute directory Department of Business Administration, Economics and Law (Business Administration and Business Education)
Verwendbarkeit des Moduls
  • Master's programme Business Administration: Management and Law (Master) >
  • Master's Programme Business Informatics (Master) >
  • Master's Programme Computing Science (Master) >
  • Master's Programme Environmental Modelling (Master) >
  • Master's Programme Sustainability Economics and Management (Master) > Basic and Accentuation 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 unlimited
Form of instruction Comment SWS Frequency Workload of compulsory attendance
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

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