R for SAS and SPSS Users, A Review

If you’ve followed me for any length of time, you’ll know that I’m a proponent of good data analysis. I was not formally educated as a programmer but I’ve found a solid understanding of data manipulation has served me well in my work as an accountant.

My primary tool for 4 years has been SAS. It is an awesome, easy to learn language that has allowed me to look like a hero on numerous projects. However, starting next week, I’m moving to a company that doesn’t offer SAS as an option. I didn’t want to lose the edge that a good analytics package offers, so I started looking around for an open source alternative. That’s when I found “R”. Like SAS, R is a statistics package. It’s designed for statisticians to perform t-tests, calculate standard deviations, and all the other black-box stuff that gives auditors the warm-fuzzies. However, like SAS, it also has strong data manipulation abilities. There is even a package called sqldf, that allows users to write SQL statements in the R command line.

Not surprisingly, because the name “R” is so generic, it is nearly impossible to find good tutorials online through tradition searching. So, I decided it was time to buy a book. Fortunately, Robert Muenchen from University of Tenn, has written a book for people exactly like me: R for SAS and SPSS Users (ISBN-10: 0387094172). Unlike a lot of programming books, Muenchen’s is packed with examples and real world applications. He walks readers through a particular scenario, then shows how to accomplish with SAS, SPSS and R. It’s like a Rosetta Stone for users needing to move from one language to the other. Overall a great help and I’d highly recommend it.