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Sebastian E. Wenz
Tel: +49 221 47694-159

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Angelika Ruf
Tel: +49 221 47694-162

Course 3: Mathematical Tools for Social Scientists: A Refresher Course with R

Prof. Dr. Oleg Nenadic

Date: 03.08 - 07.08.2020 ics-file

Location: Online via Zoom

About the lecturer - Prof. Dr. Oleg Nenadic

Course description

[This is a 24 hour class.]
This course aims to refresh mathematical concepts which are required for the understanding and the application of recent developments in empirical research methodology. The course covers the fundamentals of Mathematics (functions, linear algebra, calculus, and optimization), focusing on the understanding of the concepts. Instead of pursuing a formal approach, this course will help participants to familiarize themselves with what we consider as essential and useful mathematical knowledge. Thus, one aim of the course is to remove the commonly experienced uncertainty when researchers are dealing with mathematical concepts and expositions in their research.
An important part of this workshop is the active use of the open-source statistical programming language R. Since its introduction in the 1990s, R has become a de facto standard for statistical computing. As such, this workshop combines communicating mathematical concepts with an introduction and the active application of R, both of which are taught in parallel.
The course sessions basically comprise of two continuously alternating parts: the “theoretical part” covers the mathematical explanations while the “applied part” re-elaborates and reinforces the theoretical part by actively using R. In this way, the course lays the foundations for advanced empirical research methodology by covering the theoretical background as well as providing the participants with an insight and competence in R.
A detailed syllabus for this course is available for download here.


Target group

The course is conceptualized to support scientists who want to improve their mathematical background knowledge as a prerequisite for advanced empirical research. It is commonly found that mathematical prerequisites are an obstacle for understanding advanced statistical methods. In many cases, this may be due to the fact that the last Mathematics course has been taken at least some time ago. Thus, the course is aimed at students and researchers, especially in the social sciences, who wish to renew their mathematical competence as well as learn or fine-tune their programming skills using R.

Learning objectives

By the end of the course, participants will:
  • have an understanding of the fundamentals of Mathematics, as well as several advanced topics
  • have learnt how several basic as well as advanced statistical methods are conceptualized mathematically and how they are implemented analytically and computationally
  • give R beginners an introduction to the most powerful and universal computing tool available
  • give existing R users new insights into the R environment
Organizational Structure of the Course:  
This course is innovative in that the "theoretical" and the "practical" parts will alternate continuously and not be totally separated within each day. Typically, after a theoretical chunk (approximately 20-30 Minutes), the discussed topics will be elaborated in R in the practical chunk (approximately 20-30 Minutes). This makes the learning process dynamic, as opposed to delivering all the theory in the morning, for example, and doing the practical part separately in the afternoon. In addition, exercises for each topic will be provided, a few of which participants will have to solve during the class. Most exercises will be done after class, and participants will be strongly encouraged to solve as many of these as they can on their own after each daily session.  Problems arising from the exercises will be discussed at the start of the following day, which also provides a revision of the previous day's material before starting with new topics.


  • The only prerequisite for the workshop is the motivation to learn (or to repeat) the fundamentals of Mathematics and R.
  • Note: Familiarity with R is not a prerequisite (but highly welcome). Downloading and installing R ( and Rstudio ( prior to the course is strongly suggested. Participants are encouraged to play around with the software before the course in order to get a feeling for it.
Software and Hardware Requirements:
Required hardware:
Required software:
- R ( and RStudio ( No additional R packages are required.
Required screens and projectors:

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