Data analysis with R for Social Scientists - Einzelansicht

In this course, students will learn the basics of data analysis using the R programming language. At the end of the course, students will be able to write an empirical seminar paper or BA-thesis using quantitative statistical modeling techniques. To achieve this, we will not only focus on how to apply this techniques in R, but also why certain approaches are chosen for certain problems and how to use them correctly with the aim of producing reliable statistical results.

The course starts with an introduction to exploratory data analysis; getting to know your data, your variables and the relationships between them. After this we will we go into statistical modeling. Before we can even start to model, we have to understand what modeling is, what approaches do exist and what we should and should not include in our model. You will learn how to use acyclical directed graphs (DAGs) to construct a model based on theoretical assumptions. We continue with a thorough introduction to simple and multiple linear regression. This will be the basis for more advanced topics that conclude the course, including introductions to logistic regression, mediation analysis and prediction. The course also includes a brief introduction to fundamentals of machine learning.

The seminar will be held in english on-site and will be accompanied by a website. To prepare for the in-person sessions, one chapter has to be read each week. In the sessions there will be time to repeat the more tricky topics, go deeper into the details and discuss questions with the lecturer as well as the plenum. There will also be sessions comprised of student exercises with in-person supported by the lecturer. The course will primarily use real datasets for examples and exercises. Access to the data will be provided.

Prior knowledge in the basics of using R is required. We will not have the time to go through the basics of writing R code, using packages or handling and cleaning data in the course. We highly encourage you to go through the following introduction to R written by Prof. Dr. Jasper Tjaden. This will equip you with all R knowledge you will need to successfully complete the seminar.
https://jaspertjaden.github.io/course-intro2r/

To gain credit for the course (Prüfungsnebenleistung), you will have to complete the in-class exercises and submit them to the lecturer.

To complete the module (Modulprüfung), you will have to write a seminar paper of ~12 pages on a research question of your choosing. The paper should include some amount of theory and literature review as well as hypotheses derived from this. To answer your research question you will then have to apply the techniques that were introduced in the course and carry out a data analysis on an appropriate data set. Support in planning your papers will be provided.

Registration and withdrawal deadline in PULS for the module final examination: 16.10.2023 - 30.03.2024.