Microcredential ekomex Introduction to R

Content 

Learn the basics of programming and data analysis in R in just 2 days at #KOMEX2026, without any prior knowledge!

What Is This Course About?
The course covers the basics of programming in R: importing data, performing the necessary data cleaning and transformation steps, creating subsets or merging datasets with other external sources of data. It also teaches some basic applied tools for data analysis and hypothesis testing, such as comparing groups and regressions. Lastly, the course offers a brief introduction into data visualization (with ggplot2) and into workflows generating reports that combine code and text (with RMarkdown).

Learning Goals

  • How to use RStudio for writing basic code and generating tabular/visual outputs.
  • How to load, export, merge and subset datasets in R.
  • How to run simple statistical models in R to compare groups or to fit OLS regressions.
  • How to create simple visualizations such as scatterplots, boxplots and line charts.
  • How to use R Markdown to seamlessly weave code and text together in reports.


Recommended Readings for the Course

  • Hadley Wickham, Garrett Grolemund, Mine Cetinkaya–Rundel: R for Data Science. O′Reilly.
  • Robert I. Kabacoff: R in Action. Data analysis and graphics with R and Tidyverse. Manning.
  • Kieran Healy: Data visualization. A practical introduction. Princeton University Press.


Assignments for the Course
Synchronous sessions will involve quick exercises (not graded), done both individually and in pairs.

Schedule

  • 10:00-11:30h - Course
  • 11:30-11:45h - Break
  • 11:45-12:45h - Course
  • 12:45-14:00h - Lunch break
  • 14:00-15:30h - Course


Who Is Your Instructor?
Daniel Kovarek is a Postdoctoral Research Fellow at the European University Institute, Florence, Italy. He studies political behavior at the voter and the elite level, applying surveys, experimental and big data methods. Daniel has been teaching a wide variety of graduate-level courses on applied statistics, research design, data visualization and programming.
@kovarek.bsky.social

Bildungszeit (can be claimed by employees in Baden-Württemberg) 
Anforderungen des Bildungszeitgesetzes Baden-Württemberg sind erfüllt
Fee 
250 EUR / Early bird 180 EUR / Please note: you will gain access to our learning management system Moodle only after having paid your course fee
ECTS Credits 
1
Contact for Questions 
komex Office
Place 
Virtual Academy
Date 
19.02.2026 (All day) to 20.02.2026 (All day)
Duration 
2 study days
Lecturer 

Dániel Kovarek, PhD

daniel.kovarek@eui.eu

Requirements 
None. The course assumes no prior knowledge of statistics, programming, or coding. Participants should have R and RStudio installed on their computer before the before, using the links https://cran.r-project.org/mirrors.html and https://posit.co/download/rstudio-desktop.