# Scientific Coordination

Dr.

Sabina Haveric

Tel: +49 (0221) 47694 - 166

var a = "<a href='mailto:";
var b = "sabina.haveric";
var c = "gesis.org";
var d = "' class='email' style='padding-bottom: 1px;'>";
var e = "</a>";
document.write(a+b+"@"+c+d+"E-Mail"+e);
Please enable JavaScript to view emails

Sabina Haveric

Tel: +49 (0221) 47694 - 166

# Administrative Coordination

Angelika Ruf

Tel: +49 221 47694-162

var a = "<a href='mailto:";
var b = "summerschool";
var c = "gesis.org";
var d = "' class='email' style='padding-bottom: 1px;'>";
var e = "</a>";
document.write(a+b+"@"+c+d+"E-Mail"+e);
Please enable JavaScript to view emails

Tel: +49 221 47694-162

Please wait...

# Course 04: Mathematical Tools for Social Scientists: A Refresher Course with R

**Lecturer(s):**

Prof. Dr. Michael Greenacre, Dr. Oleg Nenadic

Date: 05.08 - 09.08.2019 ics-file

## Course description

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 course 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.

For a full length syllabus of this course, please click here.

## Keywords

## Target group

The course is conceptualized to support social 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.

## Prerequisites

- the only prerequisite for the workshop is the motivation to learn (or to repeat) the fundamentals of Mathematics and R;
- a printed copy of the instructors' book "Mathematical Tools for Social Scientists - An introduction with R" will be distributed to every participant.

Note: Participants may bring a laptop computer in order to perform the practical exercises in this course. In the PC lab sessions however, you will have access to preinstalled hard- and software. Familiarity with R is not a prerequisite. In case you wish to work on your own computer, downloading and installing R (

__http://cran.r-project.org__) and Rstudio (__http://rstudio.org__) 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.