Maintained by Robert McDonald, Kellogg School of Management

This is a page devoted to R resources. I teach derivatives at Kellogg and have written a text that includes a tutorial on Visual Basic for Applications. After years of teaching with Excel and VBA, however, I am switching to R. I will use this page to keep track of resources I find helpful.

- Here is where you obtain the standard version of R
- Here is where you obtain RStudio, which I highly recommend.
- Organizations built around R
- Revolution Analytics provides a commercial version of R that is free for academic use. (I have not used it.) R's being open source permits the existence of multiple versions, some paid, some free.
- Rmetrics is a not-for-profit focused on using R to teach statistics and finance. They maintain a number of powerful packages.
- Rconvert, a firm assisting with conversions to R from SAS, SPSS, etc.

- R for Beginners Excellent introduction, more a reference than tutorial
- R Tutorial An on-line introduction to R with lots of examples.
- Catalog of R Graphs. Very cool, built in R and published with Shiny
- One Page R: A Survival Guide to Data Science with R This is under development but it looks very promising.
- Collection of blogs about
R This site is a content aggregator. Apparently there are a
*lot*of folks who blog about R! - Using the *apply functions This exchange on the excellent Stackoverflow site helps to clarify the differences between the various apply functions.
- R graphics tutorial. Starts simple and covers lots of graph types. Well done.
**Miscellaneous University web sites.**There are a host of sites that have course materials and collections like this page. I'm including a few here that you might want to browse.- UCLA's R Resources Page
- Princeton's
*Introducing R*by German Rodriguez -
Norm
Matloff's R web site There are only a few links here, but
Matloff is the author of
*The Art of R Programming*, which is a very good book. - Notes for an R course at UNC, by James E. Monogan III.

- Burns Statistics,
with R resources including
*The R Inferno*, an essay on pitfalls in R. - NY Times Graphics Department blog. They use R for data analysis and preliminary graphs.
- Two minute video tutorials about R.

- Problems
with Excel. This page is maintained by a biostatistician at
Vanderbilt, Frank
Harrell, who has written several R packages, including Hmisc and
rms. The latter is a companion to the book
*Regression Modeling Strategies* - When to use Excel, when to use R This is worth reading but it's a little lame. The author recommends becoming a more expert Excel user and also learning to use R.
- Stop clicking, start typing A brief presentation explaining why you should use R instead of Excel

- Matlab / R reference, maintained by David Hiebeler. This is a thorough compendium of things you can accomplish in Matlab and R, and how to do them in both lanaguages. It seems there are a few things Matlab can do that R cannot, but not many.

- Ubuntu R Blog, by Michael Rutter, for information about installation, packages, etc. under Ubuntu. Rutter also maintains the R-dev ppa. For a relatively complete R installation on Ubuntu, type "sudo apt-get install r-base* r-recommended r-cran* r-doc*"

- R for Dummies. The book is about $20 at Amazon and is pretty good. Here is a review.
- R Cookbook by Paul Teetor. This is appropriate for beginners and has lots of examples. It's a typically excellent O'Reilly book.
- R in a Nutshell by Joseph Adler. The second edition of this book is out, but I haven't looked at it closely. The first edition was an excellent general introduction to R. The presentation of statistical techniques towards the end struck me as shallow, but this is probably inevitable with a book trying to cover everything. The "Nutshell" books try to be comprehensive, and R is huge, so it's tough to be comprehensive.
- The Art of R Programming by Norman Matloff. This is not a beginner's book, but once you have used R for a while, this will help you understand why various commands work the way they do. It's clear and places R in context with other programming languages. I highly recommend it. There might be a free chapter available for download.

- Google's R Style Guide Google uses R internally, apparently enough that they find it valuable to maintain a style guide.
- R Coding Conventions: Draft Interesting document with specific recommendations for most use cases. It explains when to use capitals and mixed case, for example.
- Emacs speaks statistics This is an Emacs mode that lets you run R from within Emacs. You can use Emacs to write code and run it immediately. Output shows up in another buffer. There are more than a few simple commands --- this is an environment for editing and running R, SAS, Stata, etc. The manual is 80 pages! If you use Emacs, you should definitely have this. If you don't use emacs, ESS will not be useful.
- ess-tracebug This add-on to ESS allows you to debug R code from within Emacs. You can set breakpoints, add watch windows, etc. Again, this is only for Emacs.
- Finally, the moon landing was a hoax. All the proof you need is right here.