Comments about O'Reilly Media R Cookbook:

This is a book about how to use the R programming language to solve several statistical problems like combinations, probabilities, frequencies, quantiles, means, correlations, regressions and ANOVA analysis, and as a plus, time series analysis. This cookbook is perfect to students and professors looking for a computing tool that helps them to understand and teach statistical courses, respectively. That's because many times it is important to solve complex exercises that shows the several applications that a statistical topic, like the normal distribution, has in surveys, engineering, manufacturing and commerce, which implies performing several activities related to data retrieval, storage, processing, analysis and visualization.

This cookbook explains the how-to of such activities providing a catalog of tasks to accomplish each of these, for example, how to read and write CVS files, prepare the data contained in those files, generate random samples, calculate the probability of X, test for normality, perform linear regressions and plot the histogram. Each task is described following this structure: Problem, Solution, Discussion and See Also, being the Discussion section the valuable resource of the R Cookbook, because this section explains the implications of using the given solution together with some tips and tricks. Those implications, tips and tricks makes the difference between the R Cookbook and a raw Internet search, so students and professors can learn about the rationale of a solving a statistical problem with R, not just the syntax of variables and functions.

However, it is important to clarify that the R Cookbook is not a book for learning the essence of statistics; instead the R Cookbook is a suggested companion resource for the course main textbook. The R Cookbook will help the explanation and understanding of the core topics, exercises and applications, and simulate different problem scenarios.

Finally and personally, I'd like to see a second edition, volume or update to include how to solve operations research problems using R, if possible. For instance, simplex method, duality, transport and network problems, and inventory and queuing systems are the most common ones in operations research.

Note: This review is in exchange of the O'Reilly Bloggers Review Program (oreilly.com/bloggers).

Comments about O'Reilly Media R Cookbook:

I'm in the process of porting the statistics projects I assign to my students over to R. This book has made the process almost effortless. The book is organized wisely and the explanations and code are easily understood. Separated into chapters based on the kinds of things that can be done with R, this book helps you quickly get the job done you need to do. Both input and output are clearly shown, with a brief explanation based on the statistics behind it all.

I think it's especially useful to students who've been given a statistical analysis to do and who can use the book to figure out how to do that analysis in R. The book shares one of the reasons for using R;i.e., the ability to further explore the data by building on what we learn from previous analyses of the data. Both R and this book make it very easy to say things like, "If you split the data by gender, can you see any significant differences based on gender?"

I'd quibble a little with his explanation of the confidence interval for the mean. On p. 197 he obtains a confidence interval and says there is a 95% probability that the mean is in that interval, which I think is not quite right. Either the mean is in there or it's not! However, if we found the confidence interval 100 times using the t.test, then the mean would be in about 95 of those intervals,which I think is saying things slightly differently.

Comments about O'Reilly Media R Cookbook:

The R Cook­book by Paul Tee­tor is a solid addi­tion to the well respec­ted series. Tee­tor provides a rich col­lec­tion of use­ful examples writ­ten in the proven method and cov­er­ing everything from installing, con­fig­ur­ing and run­ning R to car­ry­ing out soph­ist­ic­ated stat­ist­ical ana­lysis tasks that demon­strate the power of R. The book is tar­geted at a wide audi­ence from R novice eager to just start play­ing in R to more exper­i­enced prac­ti­tion­ers look­ing to hone and round out their R rep­er­toire. It can be used as an intro­duct­ory train­ing source for those who like to learn by doing and extra­pol­at­ing know­ledge from examples. It also has the use­ful abil­ity of func­tion as a ref­er­ence source when plot­ting a par­tic­u­lar R exercise.
The prob­lem — solu­tion — dis­cus­sion pat­tern works well when the prob­lem is clearly and con­cisely stated as Tee­tor does. As the book pro­gresses it does move towards more advanced stat­ist­ical manip­u­la­tion and ana­lysis, but then if you are using R in the first place then this is a fairly safe assump­tion. This is one of the more not­able cook­book series for the thor­ough­ness of the dis­cus­sion. The inclu­sion of philo­soph­ical notes, para­meter and options sec­tions when neces­sary and finally the cross-indexing via the more inform­a­tion sec­tion set this book apart as a superb ref­er­ence. In con­junc­tion with the R in a Nut­shell which was reviewed earlier, there are indis­pens­able tools for the bud­ding R enthu­si­ast and in con­junc­tion with the freely access­ible R ref­er­ence manu­als from the Found­a­tion form the optimal R lib­rary.
My only gripe is that there is less focus in this book on the visu­al­isa­tion end of R. That is not to say that there not vis exer­cises in the book. Simply that it is heav­ier on the ana­lysis end on the lan­guage which is actu­ally well and good as this is cru­cial to the lat­ter and an area that I for one need the instruc­tion.
This cook­book does not expect read­ers to arrive with extens­ive R know­ledge and as I men­tioned earlier is tar­geted for a broad audi­ence of R practitioners.

Comments about O'Reilly Media R Cookbook:

Paul Teetor finally brings R to the masses! I've struggled for several months now to learn R on my own from a non-statistical background. I've struggled through several other books on R, but they never read as easily as Teetor's R Cookbook does. Coupled with O'Reilly's R in a Nutshell, if you have Teetor's R Cookbook on your bookshelf, too, R becomes a practical, useful, software tool you can become comfortable with.... even with R's steep learning curve. Teetor knocks the learning curve down to size!
Hint: 2nd edition needs more Time Series discussion!

Comments about O'Reilly Media R Cookbook:

Simply put, one of the best R starters around. What you get here are recipes for most common problems you will face while working with R. This book is an extended version of 25 Recipes for Getting Started with R. However, the coverage of material is different. While 25 Recipes focus on getting started with R, R Cookbook penetrates the subject in greater details and goes beyond simple usage of R. You will find here not only how to load data, manipulate it and plot some graphic. You can find description of various statistical analysis as well.

This book, is not for a reading in bed just before you go to sleep. It is too pragmatic. Simple definition of the problem and just after that, simple solution – that's what you get when it comes to each issue covered within the book. This is the strength of R Cookbook. On the other hand, it's weakness. If you cant find the question within table of contents it might be hard to get the answer for what you ask about. As I like pragmatic approach, I like the book as well. For me it's just perfect. Well, maybe just too short.