Module PY4101-KP08

Advanced (statistical) methods of analysis of multivariate data (Stats3Psy)


Duration

1 Semester

Turnus of offer

each winter semester

Credit points

8

Course of studies, specific fields and terms:

  • Master Psychology - Cognitive Systems 2022, compulsory, psychology

Classes and lectures:

  • PY4101-Ü: Statistik 3 (exercise, 1 SWS)
  • PY4101-V: Statistik 3 - Vorlesung (lecture, 2 SWS)
  • PY4101-S: Statistik 3 (seminar, 2 SWS)

Workload:

  • 70 hours in-classroom work
  • 30 hours exam preparation
  • 140 hours private studies and exercises

Contents of teaching:

  • Generalised linear models (e.g., logistic regression)
  • Applied multivariate statistics (Confounding, Moderation, Mediation, Causality, Bias)
  • Basics in Classification, Pattern recognition, Dimensionality reduction
  • Basics in statistical epidemiology and risk communication
  • Algebra and geometry of linear models
  • Generalized linear models (e.g. logistic regression) and hierarchical linear models

Qualification-goals/Competencies:

  • Students acquire a more profound ability in planning, analysing, assessing and interpreting scientific results.
  • Students are able to analyse complex data sets from behavioural and neuroscience with current statistical software and in doing so are able to follow exploratory and confirmatory approaches.
  • Enhanced skills in mathematical, methodological, and analytical thinking
  • A deeper understanding in terms of linear algebra and geometry of the linear model
  • Extended skill set of solving statistical problems and reaching evidence-based decisions
  • Teaching the practical application of exploratory and confirmatory analysis strategies; including ensuring the reproducibility of results (through the use of R notebooks)

Grading through:

  • written exam

Literature:

  • Fox, J. (2015) : Applied Regression Analysis and Generalized Linear Models. SAGE Publications
  • Westreich, D. (2019) : Epidemiology by Design. Oxford University Press, USA
  • Tabachnick, B., Fidell, L.S. (2013) : Using Multivariate Statistics: Pearson New International Edition. Pearson Higher Ed.
  • Wickens, T. (1995) : The Geometry of Multivariate Statistics Psychology Press.

Language:

  • offered only in German

Notes:

Admission requirements for taking the module:
- None

Admission requirements for participation in module examination(s):
- Submission of exercise sheets; active participation

Module examination(s):
- PY4101-L1: Advanced (statistical) methods of analyzing multivariate data, written exam, 90min, 100% of the module grade

Last Updated:

15.07.2025