Last week I attended a training course at The University of Sheffield, "Help ! I need to use R", which aims to "enable researchers to make an assessment of whether they want to use R". This post is a summary of what I learned on this course.
What is R?
The Comprehensive R Archive Network defines R as being "a language and environment for statistical computing and graphics". It does not define it as being a software, meaning that it is not directly comparable with statistical software like SPSS, Minitab, Stata or SAS. Instead, it is a highly tuned programming language that has the ability to do statistical calculations. Different R packages are collections of coded procedures usually created by a third party.
Why use R?
- It is free when other methods of doing statistics can require a license
- It can create journal quality graphics (e.g. the package ggplot2 is one of the most advanced and flexible package for the production of graphs)
- Because it is what it expected of you. Maybe it is common in the type of journals you are interested in publishing in or maybe your supervisor prefers the use of R
How to Download R
If you are using a managed computer at The University of Sheffield, the Software Download Centre can allow you to download R. On your own computer, one place to download R is from Bristol University. You can then download extra packages which contain functions to do statistics.
- MASS- package associated with Modern Applied Statistics
- Psych- functions are primarily for multivariate analysis and scale construction using factor analysis, principal component analysis, cluster analysis and reliability analysis
- Car- companion to applied regression
- Multcomp- multi-comparison in ANOVA
- Advanced plotting packages- Lattice, ggplot2
Some places to get help
- In R type: help()
- Helpful book- R in Action by Robert Kabacoff
- Use the Quick R website
- Google it! e.g. "r ggplot2 box plot"