Microcredential komex: Probability Theory for Empirical Social Research
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This course introduces students to probability theory, which is essential to fully understand quantitative research in the social sciences.
What Is This Course About?
Many students are not systematically trained in probability theory, which is key to fully understanding quantitative research. Do you struggle with parts of econometrics because you are unfamiliar with the underlying assumptions? Would you like to more comprehensively and thoroughly understand the probability distributions that are the very foundation of statistical analysis? This five-day in-person course introduces students to probability theory, which is the foundation of state-of-the-art quantitative research in
the social sciences. We will emphasize the basics of probability theory, discuss various probability distributions and their characteristics, and show how probability theory relates to statistical analysis.
Learning Goals
By the end of the class, students will be able to
- understand the basics of probability theory, which is the foundation of modern social research,
- describe various discrete and continuous probability distributions that are frequently used in statistical analysis,
- make a connection between (the more abstract) insights from probability theory and (concrete) applied quantitative research,
- take further courses in statistics that often necessitate a certain level of understanding of probability without providing it directly to the students.
Assignments for the Course
- Final Exam (60 minutes).
- Examination: There will be a final (60-minute) written examination on Friday (1 March 2024), the last day of the course, from 15:30-16:30h.
Recommended Readings for the Course
- Moore, W. H., & Siegel, D. A. (2013). A mathematics course for political and social research. Princeton University Press. [Chapters 9-11]
- Cunningham, S. (2021). Causal Inference: The Mixtape. Yale University Press. [Chapter 2: "Probability and Regression Review"]
Who Is Your Instructor?
Jan Vogler is an assistant professor of quantitative social science at the University of Konstanz. In his research, he uses state-of-the-art quantitative tools and causal inference research designs to address major questions in the field of political economy. He teaches courses on mathematics, causal inference in political science research, and political economy (for details, see here). His work has won multiple awards, including MPSA's Kellogg/Notre Dame Award for the best paper in comparative politics (for Pandemics and Political Development) and the SAGE Award for the best article in European Union Politics (for Does EU Funding Improve Local State Capacity?).
Twitter: @Jan_Vogler