TUM|Stat recommends the use of the statistical programming environment R. The software is freely available under the GNU General Public License.
The software RStudio provides an integrated development environment. The RStudio team supports a number of R packages. Particularly noteworthy are the packages knitr and rmarkdown. Both enable the documentation of reproducible research results in a simple manner.
Literature (on R and statistical methods implemented in R):
- Bretz, F., Hothorn, T. and Westfall, P. (2010). Multiple Comparisons Using R. Chapman & Hall/CRC.
- Crawley,M.J. (2012). The R Book. Wiley, 2nd edition.
- Field, A., Miles, J. and Field, Z. (2012). Discovering Statistics Using R. SAGE Publications.
- Gałecki, A.T. and Burzykowski, T. (2013). Linear mixed-effects models using R. Springer.
- Hothorn, T. and Everitt, B.S. (2014). A Handbook of Statistical Analyses Using R. Chapman & Hall/CRC Press, 3rd edition.
- Wickham, H. (2009). ggplot: Elegant Graphics for Data Analysis. Use R. Springer.
- Xie, Y. (2013). Dynamic Documents with R and knitr. Chapman & Hall/CRC.
A lot of other titles can be found on Books related to R.
Note: Consultation requests that refer to other statistics programs can, of course, be submitted anyway. In a joint appointment it will be clarified to what extent TUM|Stat can help in this case.