Free PDF Data Analysis and Graphics Using R: An Example-Based Approach (Cambridge Series in Statistical and Probabilistic Mathematics)
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Data Analysis and Graphics Using R: An Example-Based Approach (Cambridge Series in Statistical and Probabilistic Mathematics)
Free PDF Data Analysis and Graphics Using R: An Example-Based Approach (Cambridge Series in Statistical and Probabilistic Mathematics)
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Review
"I would strongly recommend the book to scientists who have already had a regression or a linear models course and who wish to learn to use R. I give it a strong recommendation to the scientist or data analyst who wishes to an easy-to-read and an understandable reference on the use of R for practical data analysis." R News"The style of the book is a commendable "learn by example" - each of the many statistical techniques is centered on real-world examples. The collective of topics is eclectic and the book also comes with extensive R code." Carl James Schwarz, Biometrics
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Book Description
This third edition of the popular guide to using R reflects recent improvements to the R system, including major advances in graphical user interfaces and graphics packages. It emphasizes hands-on analysis, graphical display and interpretation of data. Ideal for researchers, students of applied statistics, and practising statisticians.
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Product details
Series: Cambridge Series in Statistical and Probabilistic Mathematics (Book 10)
Hardcover: 549 pages
Publisher: Cambridge University Press; 3 edition (June 7, 2010)
Language: English
ISBN-10: 9780521762939
ISBN-13: 978-0521762939
ASIN: 0521762936
Product Dimensions:
7.2 x 1.2 x 10.2 inches
Shipping Weight: 3 pounds (View shipping rates and policies)
Average Customer Review:
4.2 out of 5 stars
17 customer reviews
Amazon Best Sellers Rank:
#578,494 in Books (See Top 100 in Books)
I found this book to be quite useful for learning R, and for pointing out the pitfalls for new users. It's especially good to know that there is a website associated with the book that will allow you to download the code used in the book.There are several good free R resources out there, but in the end I think you get what you pay for. In this case it was nice to have a hard-bound reference with an index and appendix that I could highlight and dog-ear.I mostly used it as a book for learning R, and not as a stats book. I did notice that there were many good examples of common statistical applications, such as t-stat tests, residual plotting, and the like. In other words, I feel like I got my money's worth by just using a few chapters and the appendix.
Una buena ayuda al lado de mi computadora, lo uso para hacer descripción de información.
I am using this book as my main resource to learn R from scratch. I had no prior experience with the program. The text is easy to read, and gives you just enough statistical theory to understand the operations without weighing you down with overly-difficult concepts. Many useful 'references for further reading' are scattered throughout if you want to know more about any particular method or operation. The book has an accompanying website with examples of code used for all the figures in the book, solutions to selected exercises, and other helpful things. Advanced topics/sections are marked with an asterisk, indicating that a first-time reader may skip over them until a later date. Overall, the book is very explicit about the code used for all the examples, allowing for easy adaptation to the users' purposes. The exercises at the end of every chapter can be quite challenging, as they often build on concepts presented in the chapter rather than simply reviewing the material. The index is very good (there is one for terms and one for R symbols and functions). Overall, the book is pretty user-friendly for a novice like me, and it covers a broad range of methods of data analysis.
I go back to this book again and again. I never had formal training in R or statistics. This one gives you an introduction to both. Enough depth so that you feel confident to use R and somewhat more advanced statistical analyses in everyday science work.
I got this book over Crawley's (The R Book) since the Amazon reviews said that this one was more organized than Crawley's.. however, even if that is true (maybe.. but Crawley's organization does not bother me), this book does not have half of what "The R Book" has, and their GLM chapter is a poor explanation of the function.I highly recommend purchasing Crawley's book over this one. This one is not horrible, but was not sufficient for me. Lucky for me I have online access to Crawley's book for free, which has saved me in some spots, along w/ the online R-help websites and list serves.This book definitely doesn't hurt to have though, but if you are looking to only buy one book, I would not rely solely on this one.
It seems that most introductory R books spend too much time with correlations and other modeling. I am still hoping to find an R book that deals primarily with data manipulation and descriptive graphics at an intro to intermediate level. Simply put, knowing something well and conveying it properly to your audience are often mutually exclusive.
Easy-to-follow tutorials for anyone who has had one or more classes using R.
This book is very useful for wrtiting R code. I suggest it to anyone who wants to learn R or anyone going into statistics.
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