Data Analysis Using R

The module is divided into two parts. In the first half of the semester, students learn the basics and core components of data analysis with R in a lecture. The lecture covers the most important steps of data analysis projects: from importing and preparing raw data, explorative data analysis and visualization, formulating the empirical model to communicating the results. Practical examples will show how these steps can be implemented using a set of R packages known as the tidyverse. In addition, it will be shown how to generate reports in R using the open-source scientific and technical publishing system Quarto. A special focus of the lecture is to introduce students to collaboration via version-controlled remote repositories. For this purpose, students will be shown how to create and manage a repository using GitHub. In the second half of the semester, students will work independently in groups on their own data analysis project. Based on the content of the lecture, a GitHub repository will be created in group work, which the students will use to prepare a data set and perform an econometric analysis. At the end of the semester, the students will share the results of their work in a presentation created with Quarto.

Script and supplementary materials for the lecture as well as exercises will be provided on Moodle

Detailed description in the module handbook.