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Overview
R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues.
R is the fastest growing statistical software/language and is rapidly overtaking all others (e.g. SPSS, STATA, & SAS in popularity and use.) For a view of where it's come from, check out R: Past and Future History (from 1998).
RStudio Desktop is a powerful and productive user interface for R. It’s free and open source, and works great on Windows, Mac, and Linux.
Contents
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Through our licensed access to Lynda.com, you can get go through may access the 2+hour 
"Up and Running with R" and/or try a more detailed (6 hr) look via training "R-Statistics Essential Training" (This one includes a bit on RStudio as well. RStudio is a convenient and free interface to R that makes it easier to navigate.)
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- Laura Chihara's basic handouts for getting started with R: http://apps.carleton.edu/curricular/math/resources/rcomputing/
- A wealth of Online Learning opportunities identified by RStudio.
- In particular, read the R Style Guide for advice on how to write readable, maintainable code. (This is how other R users will expect your code to look when you share it.)
- RStudio: Support & Documentation
- Open Learning Initiative free course on Probability and Statistics (in which the assignments may be completed using R.) From Carnegie Mellon University. = A general introduction to probability & statistics course so it's good for people who need to brush up on this while learning R.
- A (very) short introduction to R (and Rstudio) = A 12 page pdf.
- QuickR = Helpful place to find examples of commonly used code, especially for data manipulation.
- UCLA's Resources for learning R = This includes an outrageously helpful table of Data Analysis Examples (in multiple languages.)
- CRAN is a network of ftp and web servers around the world that store identical, up-to-date, versions of code and and documentation for R (Manuals).
Avril Coghlan maintains these 3 HTML or PDF "books":
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