Computing in R (Amsterdam UMC Doctoral School)
This course is part of the PhD course program of the Amsterdam UMC Doctoral School.
- Location: Lecture hall 1 (Mo, Tu, Th), lecture hall 5 (Fr); AMC
- ECTS: 0.4
- Teachers: Perry Moerland (coordinator, p.d.moerland@amsterdamumc.nl), Aldo Jongejan, Michel Hof and Rodrigo Garcia Valiente
Goal
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.
Scheduled dates
Edition : 10-14 June, 2024
Register via the Amsterdam UMC Doctoral School.
Schedule (June 2024 edition)
Location | Day | Time |
---|---|---|
Lecture hall 1 (AMC) | Monday June 10, 2024 | 10am-1pm |
Lecture hall 1 (AMC) | Tuesday June 11, 2024 | 10am-1pm |
Lecture hall 1 (AMC) | Thursday June 13, 2024 | 10am-1pm |
Lecture hall 5 (AMC) | Friday June 14, 2024 | 10am-1pm |
Course material (June 2024 edition)
- Handouts: PDF
- Slides: PDF, Graphics
- Computer exercises: HTML, PDF
- Computer exercises with answers: HTML, PDF, R code, RMD
- Demo code: R code, RMD, HTML
Datasets for exercises
- titanic3.dta
- titanic3select.txt (right click followed by ‘save link as’)
- titanic3.xls
- titanic3select_corrected.txt (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
- Manuals
- An introduction to R (html): R in 100 pages
- R reference card: R in 6 pages
- Useful cheat sheets (for example, for ggplot2 and importing and transforming data via tidyr and dplyr) provided by the people at RStudio
- An on-line version of the book ggplot2: elegant graphics for data analysis
- Further pointers
- Editors
- Miscellaneous
- Examples of beautiful figures and corresponding R code