Teaching

Most of my teaching these days is at the MA and PhD levels and in the area of political methodology. Here, I seek to teach the students the methodological state of the art as well as reproducible scientific practices. Much of my emphasis is on research design and measurement but, of course, data analysis receives ample attention as well.

Next to teaching at the University of Zurich, I am a frequent guest at the Essex Summer School in Social Science Data Analysis. In the past, I have also taught at the ICPSR Summer School.

On this page, you’ll find some of my teaching materials. Please consult the home page of the chair of political methodology to see what courses I am currently offering.

Teaching Materials

  • Mathematics

    Some lecture notes and scripts on mathematics.

    Here, you’ll find teaching materials on the mathematical foundations of quantitative research.

    • Steenbergen, Marco R. 2019. Matrices and Their Statistical Applications. Zurich: IPZ. [matrices]
  • Programming

    Some lecture notes and scripts on statistical programming.

    Notes, Scripts, and Code Snippets:

    • Steenbergen, Marco R. 2012. A Primer of Maximum Likelihood Programming in Stata. Zurich: IPZ. [mlestata]
    • Steenbergen, Marco R. 2019. A Primer of Maximum Likelihood Programming in R. Zurich: IPZ. [mler] [lrtest] [waldci]
  • Statistics

    Some lecture notes and scripts on machine learning, statistical modelling, and the like.

    Notes and Scripts:

    • Steenbergen, Marco R. 2018. An Introduction to Principal Component Analysis. Zurich: IPZ. [pca]
  • Bayesian Inference
  • Causal Inference
  • Choice Models
  • Experimental Design
  • Machine Learning
  • Maximum Likelihood
  • Measurement
  • Multilevel Analysis
  • Reproducible Workflows
  • Survey Research