Introduction to R
Aims
- Introduction to R and RStudio
- Overview of how to use package extensions
- Getting data in and out of R
- Data exploration (basic descriptive statistics and other functions) and data manipulation
- Working with factors, dates and times
- R Graphics (base graphs vs. ggplot)
- Dynamic reporting with RMarkdown
Information
The open-source software environment R (www.R-project.org) 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 data analysis – an attractive basis for thorough exploration of your data. Furthermore, it provides a powerful programming language coupled with flexible graphical capabilities.
In this introductory course, you will learn the basics of working with data in R. For example, getting data in and out of R, data exploration and manipulation using R (recoding, transforming and aggregating data, combining data sets, ...) and creating powerful data visualizations with R. In addition, you will learn how to create dynamic reports and presentations with R Markdown.
The application of these techniques will be illustrated by practical R examples, and there will be time for students to gain practical experience with R by conducting analyses as exercises, with the lecturers being available for assistance. Upon completion of the course, you will be able to incorporate the power of R into your research.
Assessment
- Homework in the form of practical analyses in R
- Presentation and discussion of the homework in the form of an R Markdown report.
Materials
Course notes will be provided.
There are no prescribed books. The following book is recommended to interested students as further reading material:
- Wickham, H., & Grolemund, G. (2016). R for Data Science. O'Reilly
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 timetable for this course can be found here.
ERIM PhD candidates 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 (1 ECTS).
