I mainly teach classes in statistics and research methods of psychology, for both undergraduate and graduate students. Overall, since 2011, I have taught 49 classes, out of which 14 (N = 178) were evaluated. Students graded me with an average of 1.53 (N=163, SD between classes = 0.19; grades go from 1 = very good to 6 = unsatisfactory), while the topic of the class received an average grade of 1.72 (N=168, SD = 0.31).

I supervised 16 students for their thesis and currently supervise 4 students.

Research Methods (Bachelor)

Methods I

This is what I taught most, so I have a good collection of teaching material. This material (in German!) is published under a CC license through KDP as a print version at: https://amzn.eu/d/50tjI7G, as well as a pdf through google play at: https://play.google.com/store/books/details?id=2uOUEAAAQBAJ. It contains 113 exercises for the following topics:

  • everyday psychology versus scientific psychology
  • philosophy of science
  • measuring and testing
  • observation and questionnaires
  • experiment, descriptive statistics
  • correlation
  • regression
  • probability theory
  • logic of significance tests
  • confidence intervals
  • meta-analysis

Methods II

I have similar experience with teaching Methods II, but it covers many more topics. At the moment, the teaching material for research methods II is only available for students participating in the course. They include the following topics: contrast analysis, dependent samples (t-test, ANOVA, contrast analysis), non-parametric tests, factor analysis, cluster analysis, non-linear relationships, explorative data analysis, and limitations of significance testing.

I plan to make a book out out of this in the future.


For my R courses I use my own learning site: https://rlernen.de as well as a book I co-authored (again all in German):

Datenanalyse mit R: Fortgeschrittene Verfahren, Burkhardt, Titz, Sedlmeier, Pearson Studium Psychologie, (ISBN-10: 3868944133, ISBN-13: 978-3868944136)

It covers more advanced topics and includes a comprehensive chapter on multi-level modeling. You can buy it anywhere where books are sold and also directly from Pearson: https://www.pearson.de/datenanalyse-mit-r-fortgeschrittene-verfahren-9783868944136

Research Methods (Master)

I taught method classes for gradudate students including the following topics: computer simulation (e.g. artificial neural networks, cellular automata), structural equation modeling and mixed models.

I also gave sessions on mixed models and formal modeling in psychology as part of a lecture on research methods for Master students.

In addition I taught a course on artificial neural networks for graduate students (together with Prof. Dr. Peter Sedlmeier).


Check out my Youtube-channel for research methods and R:


This one is mixed English and German, but the majority is in German.

Teaching Approach

Often my exercises are based on real-world problems of psychological science. This might not be very surprising but I see many other instructors who just invent really bad fake studies or fake data. In my opinion this is not he ideal learning experience.

Klaus Grawe studied the mechanisms of psychotherapy and found that problem actuation is an important factor. It basically means that you have to experience a problem first-hand in a real setting to overcome it. Psychotherapy is not that different to learning in general; in both cases you are trying to change behavior. To achieve problem actuation, I try to use real papers in my seminars. In the end this is what scientists will face: they have to read the literature and understand it, including methods and statistics. I believe this approach is necessary to really understand what science is about, which problems scientists face and how they use the available research methods to overcome them.

Other Teaching topics

In addition to the above courses I also have enough experience to offer:

  1. An introdcutory course on mixed models (aka HLM, multilevel modeling) in R or with my own free tool https://mimosa.icu
  2. advanced R courses with emphasis on
  • programming (e.g. OOP, functional programming, getting your package into CRAN or Journals)
  • more efficient analysis with the help of tidy, reshape, plyr, dplyr
  • producing high quality plots with ggplot2
  1. courses on programming psychological experiments
  • with psychopy (including eye-tracking experiments)
  • with jspsych (for online experiments)