- Hardcover: 1076 pages
- Publisher: Wiley; 2 edition (December 26, 2012)
- Language: English
- ISBN-10: 0470973927
- ISBN-13: 978-0470973929
- Product Dimensions: 7.5 x 1.8 x 9.7 inches
- Shipping Weight: 4.8 pounds (View shipping rates and policies)
- Average Customer Review: 49 customer reviews
- Amazon Best Sellers Rank: #93,006 in Books (See Top 100 in Books)
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The R Book 2nd Edition
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“I consider this a must-read book for its content, writing, and organization." (Computing Reviews, 7 August 2014)
“Presents a fully revised and updated bibliography and reference section. Is supported by an accompanying website allowing examples from the text to be run by the user.” (Zentralblatt Math, 1 August 2013)
“Overall, The R Book (Second Edition) is a great guide to the vastly powerful and constantly evolving software that is R. It is very close to a complete reference-the coverage is excellent. For most users of R, having this book as guide will make life with R much easier, and learning to master it much faster.” (Nekkidblogger.com, 30 April 2013)"It is a classic that does not just sell to students during term time but has a much wider appeal ... This edition will sell really well on publication." (The Bookseller, 16 December 2011)
From the Back Cover
Hugely successful and popular text presenting an extensive and comprehensive guide for all R users
The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research.
- Features full colour text and extensive graphics throughout.
- Introduces a clear structure with numbered section headings to help readers locate information more efficiently.
- Looks at the evolution of R over the past five years.
- Features a new chapter on Bayesian Analysis and Meta-Analysis.
- Presents a fully revised and updated bibliography and reference section.
- Is supported by an accompanying website allowing examples from the text to be run by the user.
Praise for the first edition:
‘…if you are an R user or wannabe R user, this text is the one that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R.’ (The American Statistician, August 2008)‘The High-level software language of R is setting standards in quantitative analysis. And now anybody can get to grips with it thanks to The R Book…’ (Professional Pensions, July 2007)
Top customer reviews
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The author has not presented ideas in order in chapter 2 "Essentials of the R Language". There are several commands that are used before they are explained.
The author also refers to examples that are given in later chapters to explain R commands in chapter 2 (like lm command). I find this unnecessary since those commands could have been explained once the theory is explained.
The data files used in the book are tricky to find. Some of the files are missing from the main zip file that you find when you google for "data for the R book". Further googling helps you figure out that you can get the individual data files using "www . bio . ic . ac . uk/research/mjcraw/therbook/data/FILENAME" (remove the spaces; I have to include them since Amazon strips URLs) where FILENAME is the filename used in the book like "C:\\temp\\FILENAME".
Also it is a heavy 1000+ page book, so if you are thinking of lying down on your bed and having a relaxed read, then forget it :-)
If you want a more pleasant introduction to R, go through Roger Peng's R Programming course on Coursera, do the swirl exercises mentioned in that course and then tackle this book.
However, the book covers a lot of ground, so it will be very useful for intermediate and advanced users who already know some R and some statistics.
I also like that the author has included the output of the commands, so you don't need to necessarily type the commands to see the output. The book has graphics in color and this is quite pleasing.
BUT, you must be VERY CAREFUL, and the reason I am writing any review is my frustration has reached its threshold with this text:
From chapter one to the very last.
Prime example - page 457:
r^2 = (SSY − SSE)/SSE is what you're given at the top of the page.
If you're confused, you only have to wait til the bottom of the page: r^2 = SSY = SSE / SSY
But look! Even the corrected equation (SSY is the denominator, not SSE in r^2) has a typo! (An equal sign instead of a minus between SSY and SEE on the numerator.
This part of the chapter was just showing the long-way for the sake of concept, and eventually gives you the shorthand for R (since lm(y~x) calculates all these for you right from the get-go).
You can find these in every chapter. If you already know the concepts, you can ignore most of these as you're probably just jumping to relevant chapters to find the code functions you need, but if you're someone learning and following every letter the book says, you're going to end up with so many confusing results and errors in the program. Also, do not copy codes straight from the book, I don't know if it's due to updates or sloppy coding, but a majority of the time these will not work without modification (which requires you to already know what you're doing).
This is the greatest offense of the book, others include straight copy-paste from function help files - which makes a book you pay for a little pointless/frustrating. Also, while there's very comprehensive explanations for some concepts - Regression for example is very well covered in the book despite its typos - and absolutely no explanation for others. Or, it explains concepts for a certain analysis entire chapters after you've already used them (Ex: For loops). This last complaint just makes the logic and flow of the book frustrating, and results in a lot of chapter jumping just so you can try to move forward. Also, for what is a book about R - not necessarily quantitative analysis, there's actually extremely little time spent exploring the syntax of the language, or possible problems you may run into with each new function you learn. This makes the book only useful for those who already know R, but would like titled chapters to flip to to know what direction to start going for certain analyses.
I don't intend to be rude, I've simply become frustrated by parts of this book when otherwise it would be a great text, so I'm just not comfortable providing this to students absolutely new to R. I don't doubt the expertise or ability of the author, this book just feels like it was thrown or pieced together with absolutely zero proofreading...
Most recent customer reviews
At first glance, you would guess the first 7 chapters are for R beginners to learn the...Read more