The examples on this site aim to show how a number of common data analysis tasks can be performed using the R environment for statistical computing. The focus is on basic statistical methods for the social and life sciences. The examples assume a reader who is already familiar with the statistical underpinnings, and who knows when a particular analysis should be carried out.

The posts on this site were created automatically from R markdown documents, using a workflow that makes use of knitr, the static site generator nanoc, and the Bootstrap framework. For details, see this page explaining the workflow. This website, including all examples (R markdown, markdown, and plain R code files), is available on GitHub. The repository also contains the Makefiles and an R-script necessary for automatically building the website.

All content on this site is licensed under the Creative Commons BY-SA license.

- R Basics
- Descriptive statistics
- Work with data frames
- Univariate methods
- Nonparametric and resampling methods
- Multivariate methods
- Diagrams

The examples mostly come from my book, and are currently bare-bones R code.

Some methods within the intended scope of this repository are currently missing:

- Psychometrics (classical test theory and item response theory)
- Cluster analysis and other classification techniques
- Time series

Contributed examples are very welcome, please contact me if you would like to add your code to this repository.