Unser Lehrportfolio an der TUM

Wintersemester

Empirical Research in Management and Economics is a Master's course that covers the most important aspects of empirical research, including research design, data collection, data analysis, and interpretation.

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R for Data Science is a Master's course that equips students with core data science skills such as data wrangling, data analysis, and programming techniques.

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Judgment and Decision Making is a Master's course that reviews central empirical findings in decision research and the key theoretical approaches to analyze, understand, and evaluate decision making.

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Models in the Study of Human Behavior is a Master's course that discusses the utility and limitations of formal modeling approaches in the study of human behavior.

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Sommersemester

R for Data Science is a Master's course that equips students with core data science skills such as data wrangling, data analysis, and programming techniques.

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Introduction to Bayesian Data Analysis is a Master's course where students learn to learn with the help of Bayesian statistics and a modern scientific data analysis workflow.

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Applied Statistics in R is a Master's course in which students learn about advanced statistical techniques (e.g. nonlinear and logistic regression, penalized regression, and time series analysis) for different research questions.

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Replicability, Robustness, and Reproducibility in Behavioral Research is a Master's course that discusses the history and causes of the replication crisis as well as recent developments and proposals towards more reliable, robust, and transparent sciences.

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Process Tracing is a Master's course that provides knowledge about existing process-tracing methods and their functionality regarding the measumerent of predecisional information search and processing. 

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PhD Kurse

Bayesian Data Analysis and Cognitive Modeling is a PhD course that introduces Bayesian statistics as a tool for analysing data and estimating parameters of cognitive models using statistical software.

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