Advanced Data Analysis with R


The open-source software environment R ( is a powerful platform for data analysis and statistical graphics that has become the global standard in statistical computing. R houses an ever-growing extensive collection of tools for statistics and data analysis – an attractive basis for thorough exploration of your data. Furthermore, it provides a powerful programming language coupled with flexible graphical capabilities.

This follow-up to the introductory course will focus on programming in R. Basic programming concepts will be covered, such as accessing and altering parts of objects, controlling the order of computations, iteratively performing tasks using loops, and writing functions. We will also take a look at functional programming, and how to use these tools in practice. For example, and time permitting, it will be illustrated how these tools can be utilized when using R to scrape data from the web.

Upon completion of the course, you will be able to use the power of R’s programming language for advanced analytic tasks to improve the quality of your research.


  • Data structures and subscripting
  • Iteration using loops
  • Control statements
  • Writing functions
  • Functional programming


  • Homework in the form of practical analyses in R, which need to be prepared as an R script.
  • Presentation and discussion of the prepared R script in the form of a short report.


Course notes will be provided.

There are no prescribed books. The following books are recommended to interested students as further reading material:

  • Wickham, H., & Grolemund, G. (2016). R for Data Science. O'Reilly
  • Wickham, H. (2014). Advanced R. Chapman and Hall/CRC.

Additional info

The course will be taught in English and is limited to 25 participants. Students are required to bring their own laptops to class (R and RStudio can be installed for free). The introductory R course is a prerequisite for this course. Exemptions from this requirement can be requested from the course's contact person.

The timetable for this course can be found in the EUR course guide.

ERIM PhD candidates and Research Master students can register for this course via Osiris Student.

External (non-ERIM) participants are welcome to this course. To register, please fill in the registration form and e-mail it to the ERIM Doctoral Office by four weeks prior to the start of the course. For external participants, the course fee is 260 euro per ECTS credit.