R Environment

R is one of the more commonly used statistical analysis software. The ease with which methods can be prototyped and brought to production makes it very popular for research. The fact that it is open source, and free to use also contributes to its appeal.

The official manual for R is available here. I recommend reading at least some of it to get used to the language. If this is your first programming language, a small foray into python using google’s online python class might also do some good.

There are IDE’s (Integrated Development Environments) to use with R to make your life easier. Of these, the one I recommend is Rstudio. The use of an IDE is optional, but if you do a lot of coding it will make your life easier.

The official websites are as follows:

R – http://www.r-project.org/

Rstudio – http://www.rstudio.com/

Using Rstudio also gives you easy access to the document publishing abilities of \text{\LaTeX}. Within Rstudio, you can encapsulate R code into “chunks”, which will generate results and be placed into the typeset paper. This is made possible with plugins in Rstudio called Sweave or knitr. See more on the appropriate tutorial page.