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)
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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,
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First Sentence
Statistics is fundamentally concerned with the understanding of structure in data. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
Statistics is fundamentally concerned with the understanding of structure in data. Read the first page
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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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Most Helpful Customer Reviews
8 of 8 people found the following review helpful
By A Customer
Format:Hardcover
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.
5 of 5 people found the following review helpful
Format:Hardcover
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.
5 of 5 people found the following review helpful
By A Customer
Format:Hardcover
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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Most Recent Customer Reviews
5.0 out of 5 stars
bible for learning R!
comprehensive and easy understandable handbook for learning R.
both suitable for statisticians and non-specialists.
both suitable for statisticians and non-specialists.
Published on 28 July 2010 by Lynn Liu
2.0 out of 5 stars
Modern Applied Statistics with S Review
This book guides the reader through the mechanics of how to perform statistical analyses in R and S-PLUS, with many worked examples. Read more
Published on 4 Dec 2004 by "jbrent15"
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