Since its release in 1997, R has emerged as a popular tool for statistical analysis and research. The flexibility and extensibility of R are key attributes that have driven its adoption. Some of the advantages of R are related to the command line interface (CLI) form in which it is used. However, this does add to the challenge of learning to use R. The goal of this course is to build familiarity with the basic R toolkit for statistical analysis and graphics.

R is a flexible and powerful toolkit, but the learning curve can be pretty steep, especially at first (I can remember quite well the frustration I experienced when I first started using R!). These lessons will teach many of the basic tools included in R, and teach you how to *keep learning* how to use R.

Remember that R is much more than a "statistical package" - R is a *language*. I find that I am less frustrated with some of the foibles of R when I remember that it is a *language*, and that while mastering a language takes years of study and practice, you can quickly learn the minimum that you need to do your simpler common tasks.

You can download R from CRAN (the Comprehensive R Archive Network).

I also suggest that you download and install RStudio, which creates a nicer user interface for R. RStudio is not necessary, but once you have used it, you probably won't want to use R without it. Note: If you dont have privileges to install RStudio in lab PCs, it may be possible to install it on a USB drive.

You will need to download, and likely print, the course notes (Essential R) which are found on Essential R Notes page.