Course(s) offered in spring semester 2022

Lecture number
Spring semester 2022
Maximum number of participants


Day Time Recurrence Duration Room
Wed. 12:00 to 14:00 Every two weeks 03/23/22 to 06/22/22 Gebäude Madrid - MAD 130
Thu. 10:00 to 12:00 Weekly 03/17/22 to 06/23/22 Gebäude Madrid - MAD 130


Prof. Dr.Claudius Gräbner-Radkowitsch

+49 461 805 2512
Gebäude Madrid
MAD 219
Munketoft 3b
Post code / City
24937 Flensburg
Show details


Learning goals:

You will be introduced to the statistical programming language R. At the end of the course you will be able to perform all essential steps of a quantitative data analysis in R yourself. This includes:

(i)               data acquisition and preparation,

(ii)             visualization of the data on a publication-ready level, and

(iii)           analysis of the data using both traditional statistics and regression analysis, as well as modern tools from the field of machine learning.

You will learn how to write visually appealing and reproducible reports in R Markdown and use the version control system Git for (collaborative) code development.

Type of examination:

Your final grade is composed of:

-        Two short reports comprising a reproducible data analysis during the semester (25% each; to be completed at home)

-        A final open book exam (50%)

Further information:

Students will need to bring their personal laptops to class; you will need to install R, R Studio, and Git on your Laptop. All software used during this course is free and open source. All educational ressources such as textbooks are also free and open source.


Ismai, C. & Kim, A. (2021): Statistical Inference via Data Science. Online:

Wickham, H. & Grolemund, G. (2017): R for Data Science. Online:

Hanck, C., Arnold, M., Gerber, A. & Schmelzer, M. (2021): Introduction to Econometrics with R. Online:

Wickham, H. (2019): Advanced R. Online:

More literature will be provided through the course outline [see Link above]

Course outline