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on 4 February 2005
This book is not about statistical theory. It is about how to perform modern statistical and graphical data analysis using S environment. If you do not have sufficient background in statistics you should go for something else. There are many excellent options.
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on 12 July 2006
This book is a classic. Essential for anyone working with S or R. Some statistical background and programming skills are certainly necessary. This book was written for people with some good statistical knowledge who wants to implement sophisticated analysis to their data without much fuss. The examples are clear. The book is well written and concise.
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on 24 February 2006
If you want a book on theoretical statistics, try buying a book called "Theoretical Statistics". If you want a book that covers a massive range of modern statistical methods (including linear models, generalized linear models, generalized additive models, projection pursuit, neural networks, tree methods, mixed effects models, mixture models, robust methods and others), and which contains dozens of example analyses with S, then this book is unbeatable.
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on 11 February 2016
Many packages mentioned have been substantially updated since this book was published. A number of statistical courses still refer to examples from this book, so worth finding a second hand copy if this is the case. Otherwise, avoid, plenty of better alternatives exist.
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on 28 July 2010
comprehensive and easy understandable handbook for learning R.
both suitable for statisticians and non-specialists.
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on 28 March 2016
Bought for an actuarial student in Kenya
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on 4 December 2004
This book guides the reader through the mechanics of how to perform statistical analyses in R and S-PLUS, with many worked examples. However, the authors are not very good at explaining the theory behind the methods and you would be well advised to refer to other texts in order to learn the theory first.
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