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R Cookbook

3.91 of 5 stars 3.91  ·  rating details  ·  108 ratings  ·  8 reviews
With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and outpu...more
ebook, 438 pages
Published March 3rd 2011 by O'Reilly Media (first published January 1st 2011)
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Louis
A part of the cookbook series is expected to provide a multitude of examples of useful tasks. The R Cookbook does this, but also more. This provides more, teaching about R beyond what reference books and most tutorials.

One weakness of R compared to other data analysis environments and programming languages is it's lack of coherence that comes from a central design. Instead it seems like a set of constructs, each designed differently. As an example, the multiple packages for graphic. Every user o...more
Glenn
The R programming language is well suited for exploring correlation in medium size data sets. If you already understand the null hypothesis and know which algorithms are appropriate to use for statistical variance testing, then this book will really boost your productivity with R.

If you don't have much understanding of statistics and what purpose it serves, then this is not the first book that you should turn to.
Paul Boal
As someone who isn't a practicing statistician I was blown away by how accessible and informative this cookbook was. I expected examples to be inaccessible, but the author educated me on both R and applied statistics at the same time.
Michael Bond
Seems to cover just the right topics for a book of its size. To get more info on graphics or prorgamming, you may need additional books, but this is the ideal cookbook.
Karl
Much better than "R in a Nutshell", even given what needs they're supposed to serve. Read this first if you're learning R (and already know some statistics).
Vladimir Chupakhin
It is my Top-1 recommended book for people starting to study R. Concise and with very useful examples.
Wouter
Nice recipe reference for introductory statistics measures/tests.
Sweemeng Ng
Good reference for learning R surprisingly comprehensive
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