Netherlands, Nijmegen

Introduction to Data Science with R and Rstudio for the Social Sciences

when 8 July 2019 - 12 July 2019
language English
duration 1 week
credits 2 ECTS
fee EUR 550

Whether you are a social scientist, a business analysist or a data journalist, analysing data is key to greater understanding of the world around us. Whether it’s understanding political discussions online, the diffusion of news events, or the predictive power of certain indicators, systematic analysis improves business conduct, news analysis and reporting and understanding of human behaviour in general. To be able to understand quantitative data we need tools of high quality and, if possible, for free. R and R studio are free and multiplatform software applications for descriptive analysis, predictive, and causal analysis, and are increasingly adopted software tools for Data Science in academics, and business (e.g. Microsoft, Google). R also provides numerous tools for publication ready visualization and publication of research results.

Topics that will be discussed in the course are:
•Reading and cleaning data,
•Descriptive analysis (central tendency measures, correlations) and visualization (barcharts, histograms, scatterplots etc),
•Multivariate analysis and scale construction (e.g. factor analysis, component analysis, correspondence analysis, Mokken analysis),
•Regression analysis (choosing the right model, testing for model assumptions),
•Network analysis (network indicators, visualization)

The course will be a hands-on course, meaning participants will actively work with R and Rstudio, working on assignments.

•basic understandings of statistics and methods
•laptop with at least (4Gb of RAM and a decent hard drive with 40GB of free space.
•OS: either Windows Vista or later; Ubuntu 16.04 or later; Mac OS X 10.6+

Course leader

Maurice Vergeer
Assistant Professor
Communication Science
Radboud University

Target group

Advanced bachelor, master, PhD, post-doc and professional.

Course aim

After this course you are able to:
1.Being able to distinguish between different types of quantitative data,
2.Understanding the different types of research questions,
3.Choose the right analytical tool, given a specific research question,
4.Being able to analyse the data with R, to generate answers to research questions,
5.Being able to clearly communicate the findings in tabular or visual form.

Fee info

EUR 550: Normal fee


€ 495 early bird discount – deadline 1 March 2019 (10%)
€ 468 partner + RU discount (15%)
€ 413 early bird + partner + RU discount (25%)