Research |

Teaching |

Software |

Links |

HOWTO's
# #Resources

### ASSOCIATIONS

Biomathematics and Statistics Scotland (BioSS)
British Classification Society (BCS)
Foundation for Open Access Statistics (FOAS)
International Biometric Society (IBS)
Royal Statistical Society (RSS)
South African Statistical Association (SASA)
### STATISTICS

Statistical Science Web. A Statistics portal based in Australia, with teaching and research resources, job lists, and a large directory of contact details, mailing lists, etc.
UCI Machine Learning Repository. Repository with many data sets, hosted by the University of California, Irvine.
IFCS Cluster Benchmark Data Repository. A number of high quality, well documented data sets for performance benchmarking of cluster analysis methods.
Points of Significance: Statistics for Biologists. A basic introduction to key statistical concepts for researchers in Biology, provided by *Nature Methods*.
### COMPUTING

GNU. The GNU/Linux operating system, respecting your freedom.
UNIX tutorial. Introduction to basic UNIX/Linux commands for beginner users.
R-project. Free and open-source software for statistical computing.
RStudio. Integrated development environment (IDE) for R, for improved productivity.
Quick-R. Instructions on using R to perform various statistical procedures, written in an easily accessible style.
R Markdown basics. Basic commands to get started with R Markdown in RStudio.
LaTeX wikibook. Online guide for using the LaTeX markup language to typeset documents.
### BOOKS FREELY AVAILABLE ONLINE

Large list of free programming books (GitHub). Includes books on Bash, R and LaTeX.
The Elements of Statistical Learning (2nd edition). Trevor Hastie, Robert Tibshirani and Jerome Friedman (2009).
An Introduction to Statistical Learning. Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani (2013).
Multivariate Analysis of Ecological Data. Michael Greenacre and Raul Primicerio (2013).
Biplots in Practice. Michael Greenacre (2010).
The Linux Command Line (3rd Internet edition). William Shotts (2016).
The Art of R Programming: A Tour of Statistical Software Design. Norman Matloff (2011).
Efficient R Programming. Colin Gillespie, Robin Lovelace (2017).
A (Not So) Short Introduction to LaTeX 2e. Tobias Oetiker, Hubert Partl, Irene Hyna and Elisabeth Schlegl (2014).
### BLOGS I FOLLOW

Simply Statistics
Stats Chat