A guide to using S environments to perform statistical analyses providing both an introduction to the use of S and a course in modern statistical methods. The emphasis is on presenting practical problems and full analyses of real data sets.
Modern Applied Statistics with S (Statistics and Computing)
and over one million other books are available for Amazon Kindle. Learn more
 |
| ||||||||||||||||||||||||
 Sell Back Your Copy for $7.26
No matter where you bought them, get up to 70% back when you sell your books at Amazon.com.
Used Price$38.58
Trade-in Price$7.26
Price after
Trade-in$31.32 |
Book Description
Frequently Bought Together
Editorial Reviews
Review
"Modern Applied Statistics With S meets its goal of serving as an introduction to S for new users, as well as a reference and resource for those with more S experience." Journal of the American Statistical Association, December 2005
From the Back Cover
S is a powerful environment for the statistical and graphical analysis of data. It provides the tools to implement many statistical ideas that have been made possible by the widespread availability of workstations having good graphics and computational capabilities. This book is a guide to using S environments to perform statistical analyses and provides both an introduction to the use of S and a course in modern statistical methods. Implementations of S are available commercially in S-PLUS(R) workstations and as the Open Source R for a wide range of computer systems. The aim of this book is to show how to use S as a powerful and graphical data analysis system. Readers are assumed to have a basic grounding in statistics, and so the book is intended for would-be users of S-PLUS or R and both students and researchers using statistics. Throughout, the emphasis is on presenting practical problems and full analyses of real data sets. Many of the methods discussed are state of the art approaches to topics such as linear, nonlinear and smooth regression models, tree-based methods, multivariate analysis, pattern recognition, survival analysis, time series and spatial statistics. Throughout modern techniques such as robust methods, non-parametric smoothing and bootstrapping are used where appropriate. This fourth edition is intended for users of S-PLUS 6.0 or R 1.5.0 or later. A substantial change from the third edition is updating for the current versions of S-PLUS and adding coverage of R. The introductory material has been rewritten to emphasis the import, export and manipulation of data. Increased computational power allows even more computer-intensive methods to be used, and methods such as GLMMs,
Product Details
Would you like to update product info or give feedback on images? |
More About the Author
Discover books, learn about writers, read author blogs, and more.
Customer Reviews
Most Helpful Customer Reviews
50 of 50 people found the following review helpful
Format:Hardcover
A worthy update. The authors are matter-of-fact and straightforward. I appreciate their terse style, the broad coverage, and the many examples. It's also good that they're starting to split programming material off into its own monograph (S Programming), making this book all the more appropriate for learning, although not quite beginning, statisticians. Their considerable contribution in software is also very much appreciated.
I do not agree at all with the reviewer who chided them for including R; I say so much the better for it. I very much hope that they will continue to do so.
34 of 34 people found the following review helpful
Format:Hardcover|Amazon Verified Purchase
Another reviewer wrote "I suspect most practicioners use S+". He should have been at the UserR! 2004 conference in Vienna this past March, with 500 or so enthusiastic R users including many from big industry (financial, pharmaceutical). And Ripley is the number-one contributor to the R Help mailing list by a long way. So it is completely appropriate that R is so prominant. Many of us appreciate open source not only for its cost ($0) but also its transparency. The reviewer should take another look at R.
As for the book, it is my data anlysis bible. It gets me started in a correct direction, with very well-explained and worked out examples, which I then adapt to my own datasets. The writing couldn't be clearer, and the references to primary sources as well as non-computational statistics texts I have found to be excellent. This is the one book to own if you are more than a beginner.
As for the book, it is my data anlysis bible. It gets me started in a correct direction, with very well-explained and worked out examples, which I then adapt to my own datasets. The writing couldn't be clearer, and the references to primary sources as well as non-computational statistics texts I have found to be excellent. This is the one book to own if you are more than a beginner.
26 of 26 people found the following review helpful
Format:Hardcover|Amazon Verified Purchase
The "search inside this book" feature was not available when this review was posted. Hope it helps.
CONTENTS
Introduction
Data Manipulation
The S Language
Graphics
Univariate Statistics
Linear Statistical Models
Generalized Linear Models
Non-Linear and Smooth Regression
Tree-Based Methods
Random and Mixed Effects
Exploratory Multivariate Analysis
Classification
Survival Analysis
Time Series Analysis
Spatial Statistics
Optimization
Implementation-Specific Details
The S-PLUS GUI
Datasets, Software and Libraries
References
Index
CONTENTS
Introduction
Data Manipulation
The S Language
Graphics
Univariate Statistics
Linear Statistical Models
Generalized Linear Models
Non-Linear and Smooth Regression
Tree-Based Methods
Random and Mixed Effects
Exploratory Multivariate Analysis
Classification
Survival Analysis
Time Series Analysis
Spatial Statistics
Optimization
Implementation-Specific Details
The S-PLUS GUI
Datasets, Software and Libraries
References
Index
Most Recent Customer Reviews
1.0 out of 5 stars
Great book - scandalous rendering of Kindle edition
The printed book (which I own) deserves 5 stars as a comprehensive introduction to the S/R language and statistics.
The one star concerns explicitly the Kindle edition. Read more
The one star concerns explicitly the Kindle edition. Read more
Published 6 months ago by Reinhard Seifert
3.0 out of 5 stars
No longer alone in the field
I agree with the recent reviewers who state that this book was more valuable a few years back. Now there are many R books to choose from, that describe many different techniques. Read more
Published 14 months ago by Nick2032
3.0 out of 5 stars
More valuable 5-10 years ago
New statistics books containing R code seem to be coming out weekly. At one time I used this book a lot to get ideas on R/S programs that I needed to write. Read more
Published on March 31, 2010 by Gus Harlow
5.0 out of 5 stars
Essential Reference
Who is the books audience? Its a second book. A second book to a theory book. A second book to a textbook. A second book to a your lecture notes. Read more
Published on May 17, 2008 by J. Rounds
5.0 out of 5 stars
one of the best applied books on statistics that uses S
This text is very popular and frequently cited in the statistics literature. The authors do an outstanding job of displaying modern statistical methods through the S programming... Read more
Published on February 22, 2008 by Michael R. Chernick
5.0 out of 5 stars
Excellent, but be aware of what you are buying
This is *the* book to have on S+/R. It provides excellent value for its price (indeed, any price): it is concise, broad, informative. Read more
Published on December 19, 2007 by Giuseppe A. Paleologo
4.0 out of 5 stars
A Course in Applied Statistics
I started using R to do linear modeling and found that I was using 'library(MASS)' much of the time. MASS, it turns out, stands for Modern Applied Statistics with S. Read more
Published on October 27, 2007 by James Brownlow
5.0 out of 5 stars
Great reference book
This is a great programming reference book for S-plus or R. I would imagine any serious programmer in S-plus already has this on his/her desk. Read more
Published on August 9, 2007 by Lijun Shi
5.0 out of 5 stars
a good book for learning S (and R)
for the beginners of R (and S).
Published on March 19, 2007 by Emel Oylum Yildirim
5.0 out of 5 stars
this book led me out of the wilderness of R
After weeks struggling with poor and incomplete online documentation for the R language, this book was a breath of fresh air. Read more
Published on September 10, 2006 by M. Driscoll
Citations (learn more)
1
book
cites this book:
- New Zealand English: Its Origins and Evolution (Studies in English Language) by Elizabeth Gordon in Back Matter
Books on Related Topics
(learn more)
|
