I primarily instruct courses in statistics and research methods within the field of psychology, catering to both undergraduate and graduate students. Since 2011, I have conducted 49 classes, with evaluations available for 14 of them (N = 178). Students have consistently appraised my teaching, providing an average rating of 1.53 (N = 163, SD between classes = 0.19; grades ranging from 1 = very good to 6 = unsatisfactory). Additionally, the subjects covered in these classes garnered an average grade of 1.72 (N = 168, SD = 0.31).

I have supervised 18 students in their thesis projects and am currently overseeing the work of 2 students.

Research Methods (Bachelor)

Methods I

My primary focus has been on teaching Methods I, and as a result, I have compiled a robust collection of teaching materials (all in German). This material, available under a CC license, has been published through KDP as a print version, accessible at: https://amzn.eu/d/fxOVD7m. It comprises 120 exercises covering a range of 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
  • t-test
  • confidence intervals
  • meta-analysis

Methods II

While I also have considerable experience teaching Methods II, covering a broader spectrum of topics, the teaching material for this course is currently exclusively accessible to enrolled students. These topics encompass contrast analysis, dependent samples (t-test, ANOVA, contrast analysis), non-parametric tests, factor analysis, cluster analysis, non-linear relationships, explorative data analysis, and the limitations of significance testing.

I have plans to compile this extensive material into a book in the future.


For my R courses, I rely on my dedicated learning site: rlernen.de. Additionally, I utilize a co-authored book (in German):

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

This resource delves into more advanced topics and features a comprehensive chapter on multi-level modeling. It is available for purchase at various bookstores and directly from Pearson: Datenanalyse mit R.

Additionally, I recommend the Essential R Cheatsheets, which include a Basic Stats Cheatsheet encompassing all crucial aspects of data analysis: Essential R Cheatsheets.

Research Methods (Master)

I have instructed method classes for graduate students, covering a diverse range of topics such as computer simulation (e.g., artificial neural networks, cellular automata), structural equation modeling, and mixed models.

Furthermore, I conducted sessions on mixed models and formal modeling in psychology as part of a comprehensive lecture series on research methods designed for Master’s students.

Additionally, I delivered a specialized course on artificial neural networks tailored for graduate students, co-teaching with Prof. Dr. Peter Sedlmeier.


Explore my YouTube channel for content on research methods and R:

Methodenmonster YouTube Channel

The content is a mix of English and German, with the majority presented in German.

Teaching Approach

My teaching philosophy often revolves around crafting exercises based on real-world issues in psychological science. While this may seem unsurprising, I havve noticed a trend among other instructors who resort to inventing poorly constructed fake studies or fabricated data. In my view, this approach does not provide the most effective learning experience.

Drawing inspiration from Klaus Grawe’s exploration of psychotherapy mechanisms, particularly the concept of problem actuation, I emphasize the significance of experiencing a problem firsthand in a genuine setting to effectively overcome it. This principle holds true not only in psychotherapy but also in the broader context of learning, where the goal is behavior change. To foster problem actuation, I integrate real research papers into my courses. This approach mirrors the challenges scientists encounter—reading and comprehending literature, including methods and statistics. I believe this hands-on approach is essential for a genuine understanding of the scientific process, the challenges faced by scientists, and how they utilize available research methods to surmount obstacles.

Other Teaching Topics

In addition to the previously mentioned courses, I bring ample expertise to offer instruction on:

  1. An introductory course on mixed models (also known as HLM or multilevel modeling) in R, or utilizing my own free tool at mimosa.icu.

  2. Advanced R courses, focusing on:

    • Programming skills (e.g., OOP, functional programming, submitting your package to CRAN or journals).
    • More efficient data analysis using tools such as tidyverse, reshape, plyr, and dplyr.
    • Creating high-quality plots with ggplot2.
  3. Courses on programming psychological experiments:

    • Utilizing psychopy, including eye-tracking experiments.
    • Implementing experiments with jspsych, suitable for online research.