310405 Multivariate Verfahren (V) (WiSe 2025/2026)

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This course gives a relatively broad overview of various techniques for analysing complex multivariate data. It can basically be considered an intro to machine learning from a statistical perspective. We'll focus on understanding when and why to use different methods, with examples from various domains showing how these techniques answer real-world questions.

Course content:

  • Intro and exploratory data analysis
  • Regression (focus on shrinkage methods)
  • Cluster analysis
  • Classification
  • Dimensionality reduction

Teaching staff

Dates ( Calendar view )

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Subject assignments

Module Course Requirements  
25-FS-EM Introductory Module E2: Einführende Veranstaltung aus den Fakultäten Student information
E3: Einführende Veranstaltung aus den Fakultäten Student information
25-FS-GM Basic Module E2: Einführende Veranstaltung aus den Fakultäten Student information
E3: Einführende Veranstaltung aus den Fakultäten Student information
31-M-El1 Elective Courses 1 Chosen course from the group "Specialisation and deepening of the knowledge on economic theory and/or quantitative methods" 4 LP Student information
31-M-El2 Elective Courses 2 Chosen course from the group quantitative methods 4 LP Student information
Chosen course from the group quantitative methods 4 LP Student information
31-M-ISDA Introduction to Statistical Data Analysis Multivariate Methods Student information
31-M23 Profile Module Statistical Methods Multivariate Verfahren Student information
31-SW-StaM Statistical Methods Multivariate Verfahren Student information

The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.

Degree programme/academic programme Validity Variant Subdivision Status Semester LP  
Psychologie - Strukturiertes Promotionsprogramm / Promotion Veranstalt.Forsch&Auswert-Meth   2 aktive Teilnahme  
Studieren ab 50    
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WS2025_310405@ekvv.uni-bielefeld.de
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Last update basic details/teaching staff:
Thursday, June 5, 2025 
Last update times:
Thursday, August 14, 2025 
Last update rooms:
Thursday, August 14, 2025 
Type(s) / SWS (hours per week per semester)
lecture (V) / 2
Language
This lecture is taught in english
Department
Faculty of Business Administration and Economics
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565236174