- 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: 0521762936
- ISBN-13: 978-0521762939
- Product Dimensions: 6.8 x 1.2 x 9.7 inches
- Shipping Weight: 2.9 pounds (View shipping rates and policies)
- Average Customer Review: 4.0 out of 5 stars See all reviews (14 customer reviews)
- Amazon Best Sellers Rank: #942,016 in Books (See Top 100 in Books)
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Data Analysis and Graphics Using R: An Example-Based Approach (Cambridge Series in Statistical and Probabilistic Mathematics) 3rd Edition
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"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."
"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
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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Top customer reviews
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.
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.
Logistic regression is also introduced and shown to be a member of a larger class of models called generalized linear models which differ from linear models in that the dependent variable is a transformation of the basic dependent variable. The transformation is called the link function. For logistic regression the transformation is called the logit function. Hierarchical (or multi-level)models are also considered.
There is also a chapter on classification and regression trees. The final methods chapter covers multvariate analysis including classifcation, principal components,and propensity scores. These are topics not commonly seen in a first course on regression or data analysis.
What makes the book unique is a thorough introduction to the R programming language and the presntation of every technique with examples in R that both motivate the need for the technique and the details of the implementation in R. There is a lot of R code given and references to a variety of sources for R that can be found on the internet. The book can serve both as an introduction to data analysis and a tutorial on the R programming language. This can be useful as a text for undergraduate and graduate students. It is also an excellent reference for researchers who want to use R and its application to practical problems. The book also has an appendix that shows the relationship between R and S and SPlus, highlighting the differences. The first chapter is a careful introduction to R and the last chapter covers advanced applications in R.
The graphics used throughout the book are excellently presented and there are even a few color graphs. This text has just had a second edition published but my review is based on the 2003 version which is the one I purchased.