- Series: Statistics and Computing
- Hardcover: 498 pages
- Publisher: Springer; 4th edition (September 2, 2003)
- Language: English
- ISBN-10: 0387954570
- ISBN-13: 978-0387954578
- Product Dimensions: 6.1 x 1.1 x 9.2 inches
- Shipping Weight: 1.9 pounds (View shipping rates and policies)
- Average Customer Review: 21 customer reviews
- Amazon Best Sellers Rank: #704,939 in Books (See Top 100 in Books)
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Modern Applied Statistics with S (Statistics and Computing) 4th Edition
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"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,
Top customer reviews
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The one star concerns explicitly the Kindle edition. In short: The rendering of formula and even (plain text!) S/R code is a scandal.
Formula and S/R code are included as bad resolution pictures and NOT rendered professionally in HTML5. They appear in pale grey and cannot be zoomed!
Springer has demonstrated with another Kindle book I purchased (Bapat RB: Linear Algebra and Linear Models) that they are capable of producing a professional Kindle version.
I purchased the Kindle edition in addition to the printed one, just to have it around when I need to look things up.
The same issue is valid for the Springer Kindle versions of:
Dalgaard P: Introductory Statistics with R
Zuur AF et al: Mixed Effects Models and Extensions in Ecology with R
I will repeat this statement in reviews for the above mentioned books.
When I have found out how to contact costumer service at Springer I will formally demand a refund or an update.
Do not buy the Kindle edition.
Still, this is a must have for any applied statistician.
The first five chapters are a brief overview of /introduction to S-Plus (or R). These chapters present enough information and examples to make the rest of the book fairly easy to work through.
I got the book primarily to work design of experiments. The chapters on linear statistical models and general linear models were perfectly suited to my needs. Topics like factorial experiments, random and mixed effects, nested designs, partially balanced designs are covered. In addition, techniques of robust analysis and bootstrap methods are presented.
The book covers many other areas - non-linear models, classification, time series, optimization.. I have not worked through any of these topics in the book.
Overall I find Modern Applied Statistics with S to be an excellent book, invaluable if one is using R (I don't have S-Plus) as the vehicle for analyses.
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.
The S Language
Linear Statistical Models
Generalized Linear Models
Non-Linear and Smooth Regression
Random and Mixed Effects
Exploratory Multivariate Analysis
Time Series Analysis
The S-PLUS GUI
Datasets, Software and Libraries