R is a wonderfully flexible platform and language for exploring, visualizing, and understanding data. I chose the quote from Alice in Wonderland to capture the flavor of statistical analysis today—an interactive process of exploration, visualization, and interpretation.
The second quote reflects the generally held notion that R is difficult to learn. What I hope to show you is that is doesn’t have to be. R is broad and powerful, with so many analytic and graphic functions available (more than 50,000 at last count) that it easily intimidates both novice and experienced users alike. But there is rhyme and reason to the apparent madness. With guidelines and instructions, you can navigate the tremendous resources available, selecting the tools you need to accomplish your work with style, elegance, efficiency—and more than a little coolness.
I first encountered R several years ago, when applying for a new statistical consulting position. The prospective employer asked in the pre-interview material if I was conversant in R. Following the standard advice of recruiters, I immediately said yes, and set off to learn it. I was an experienced statistician and researcher, had 25 years’ experience as an SAS and SPSS programmer, and was fluent in a half dozen programming languages. How hard could it be? Famous last words.