Paul Teetor

I picked up this book with the intention of learning intermediate R. I was past the novice stage of learning the language, but I was still short of learning Advanced R. This book gave me the confidence to read R code more quickly and to understand more nuance in this (fun) language.

This book is written by a quant (Wall Street data analyst) who has Masters degrees in both statistics and computer science. I find his statistics section interesting and most helpful. His visualization section is dated as it should use ggplot instead of R's native plotting techniques.

He analyzes several helpful methods; figuring out those methods constitutes the learning part of the book. The short script (this is a computer cookbook after all) were helpful to extend my knowledge and agility with the language.

The statistics section consists of a plethora of helpful analytical techniques to get what you want out of R. The information in this section is unique to me and as such new/useful. It tells me what techniques to use for certain types of data (e.g., normal vs. non-normal). Short of a statistics textbook, that's all you can ask for from a computer script cookbook.

So this book served its purpose well. I would not classify it as essential R reading, however. There are other texts which are more important. Some of the scripts are obvious, but this book provided good reading while I was eating lunch for a couple of weeks.
… (mais)

I agree that this is not a book for the beginners, but nevertheless it started with the very basics. I was impressed about it though it is from a Cookbook series.

The approach in the book is: if this is your problem, here's the solution, followed by a discussion which provides great amount of detail about the concept or function. This format allows the book to be used as a reference guide as well as it will assist us to jump to a point directly. The book illustrates plenty of functions of R in this fashion.

There are parts of the book that educate us about Statistics itself, but prior knowledge of some Statistics is a must if you want to make the best of this book.

The author shows examples from a variety of libraries - MASS, Cars93, zoo, XML to name a few. Enthusiastic readers will explore the data sets in these libraries and become more hands-on. The chapter on Useful Tricks exposed many of the "helper" functions. These add to the convenience while working with R.

The code samples for the book seemed incomplete when I downloaded them. But this worked for my benefit in the sense that I spent more time actually writing the code or creating the data myself - helped me get a little more comfortable around it's syntax. Blessing in disguise I guess.… (mais)