Basic Statistical methods

R is primary a statistical language - over the years it has morphed into much more – but at its heart there is a powerful engine for advanced statistical modelling and analysis. I haven’t yet explored much in the way of advanced statistical analysis in R, and much of what I have looked at isn’t really appropriate for this workshop.^fn24 In light of this, this section aims to provide a base understanding of some of the statistical functions of R. Hopefully you’ll be able to branch out and explore using R’s help system and the internet to find more statistical tests to fit your needs.^fn25

The bulk of these examples have been modified from those found at Quick-R (see references at the start of the manual for this and other useful references).

^fn24. If anyone is interested in Principle Components Analysis (PCA) I could put together a small manual with R scripts from some of the work that I’ve done. ↩

^fn25. As far as I can see there are inbuilt functions and external packages that allow R to offer all the features (and more) of software such as SPSS and Graphpad Prism – so if you use these often you could try running you’re analysis in R. ↩