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Here you'll find three documents that my colleague Paul Torfs and I wrote about learning R:

1. A (very) short introduction to R

The base document, with 10 pages of background and exercises and 2 pages listing useful functions (to use as a reference). Working through this document takes 1 to 2 hours (depending on your background). An older version of this document can also be downloaded from the R website (as contributed document): https://cran.r-project.org/doc/contrib/Torfs+Brauer-Short-R-Intro.pdf

2. Doing "A (very) short introduction to R" in the interactive swirl environment

Instead of reading the pdf and doing the ToDo exercises, you can also go through the text and exercises in an interactive environment called swirl (developed by swirlstats.com). This short manual gets you started with the (very) short introduction to R. It also points you to some nice follow-up classes created by others.

This swirl course is relatively new, so it may still contain errors. If you find any, let me know on the issues page.

3. Writing your own R scripts

After learning the basics, you have to gain experience in building R scripts. In this document you learn to set up a script step by step. The examples are from hydrology, but the exercises are useful for everyone.

4. Portable versions of R and RStudio

In case you want to take R everywhere you go (you may want to install the programs on a USB stick in case of administrator rights issues).

To learn R step by step, we made 8 self study modules of 1-3 hours (depending on your background):

1. A (very) short introduction to R
2. R Programming MOOC first part
3. R Programming MOOC second part
4. Basic plotting
5. Pretty plotting
6. Reading data files
7. Matrix operations
8. Spatial data

Modules 2 and 3 are swirl lessons belonging to the course R Programming (the credits go to the developers of that course). Modules 4-8 are script writing assignments. More information can be found in the folder called Self study modules.

Hydrology and Quantitative Water Management Group