Theo Pepler

Research | Teaching | Software | Links | HOWTO's



  • 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)

  • 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.

  • 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.

  • 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).

  • Simply Statistics
  • Stats Chat