Universität Wien

540010 SE Research Seminar (2024S)

Introduction to Bayesian Statistics in R

4.00 ECTS (2.00 SWS), SPL 54 - Doktoratsstudium Psychologie und Biologie mit Schwerpunkt CoBeNe
Continuous assessment of course work
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Friday 08.03. 15:00 - 18:15 Hörsaal A Psychologie, NIG 6.Stock A0606
  • Friday 22.03. 15:00 - 18:15 Hörsaal A Psychologie, NIG 6.Stock A0606
  • Friday 12.04. 15:00 - 18:15 Hörsaal A Psychologie, NIG 6.Stock A0606
  • Friday 19.04. 15:00 - 18:15 Hörsaal A Psychologie, NIG 6.Stock A0606
  • Friday 10.05. 15:00 - 18:15 Hörsaal A Psychologie, NIG 6.Stock A0606

Information

Aims, contents and method of the course

This course offers an introduction to Bayesian Statistics in R and covers the following topics:
- Revisiting Frequentist Statistics
- Bayes’ Theorem, Bayesian Point and Interval Estimation
- Bayesian (Informative) Hypothesis Testing using Bayes Factors
- Markov Chain Monte Carlo (MCMC) Sampling
- Bayesian Linear Regression and Mixed-Effects Modeling

Note that this is the tentative schedule for the class, and changes may be made over time depending on the class progress and student needs.

Assessment and permitted materials

Continuous assessment of coursework
Homework assignments

Minimum requirements and assessment criteria

To receive a passing grade, at least three out of five homework assignments need to be completed and submitted.

Examination topics

Reading list

Kruschke, J. K. (2015). Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan (2nd ed.). Elsevier.

Johnson, A. A., Ott, M. Q., & Dogucu, M. (2022). Bayes Rule! An introduction to applied Bayesian modeling. Chapman and Hall/CRC.

Lambert, B. (2018). A Student’s guide to Bayesian statistics. Sage.

McElreath, R. (2023). Statistical rethinking: A Bayesian course with examples in R and STAN (2nd ed.). Chapman and Hall/CRC.

Association in the course directory

Last modified: Tu 12.03.2024 08:47