Computing in R (Amsterdam UMC Doctoral School)
This course is part of the PhD course program of the Amsterdam UMC Doctoral School.
- Location: Academic Medical Center, Amsterdam.
- ECTS: 0.4
- Teachers: Perry Moerland (coordinator), Aldo Jongejan and Michel Hof
R is a simple programming language for statistical computing. Due to its flexibility and the large variety of statistical functions available in R, it is a popular alternative for programs like SPSS. However, for a beginner mastering R can be rather difficult. This course helps the student to become familiar with the basics of R. After the course the student will be able to write short programs in R for basic (data) analyses and for plotting figures.
Edition 1: 13, 14, 16 and 17 December, 2021
Edition 2: 14, 15, 17 and 18 March, 2022
Edition 3: 13, 14, 16 and 17 June, 2022
Register via the Amsterdam UMC Doctoral School.
Schedule (March 2021 edition)
|Zoom||Monday March 22, 2021||9-12am|
|Zoom||Tuesday March 23, 2021||9-12am|
|Zoom||Thursday March 25, 2021||9-12am|
|Zoom||Friday March 26, 2021||9-12am|
Course material (March 2021 edition)
- Handouts: PDF
- Slides: PDF
- Computer exercises: HTML, PDF
- Computer exercises with answers: HTML, PDF, R code
- Demo code: HTML, RMD, R code
Datasets for exercises
- titanic3.dta (right click followed by ‘save link as’)
- titanic3select.txt (right click followed by ‘save link as’)
- titanic3.xls (right click followed by ‘save link as’)
Information on R
- R homepage
- R and its packages can be downloaded from CRAN
- Introductory material
- Learn R interactively using swirl. Use their ‘R Programming’ course to refresh what you learnt in our course.
- Datacamp offers several on-line courses at the beginner and intermediate level with lots of exercises
- Cookbook for R offers many great examples
- A short introduction to R with a nice list of common error messages (and how to maybe solve them) on the last page
- Quick-R shows the commands to be used for many aspects of a statistical analysis, and has been useful information for experienced users of some other statistical packages
- Documentation for R packages organized by topical domain
- Further pointers