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Modern Applied Statistics with S (Statistics and Computing)
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Produktbeschreibungen
Pressestimmen
"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
Kurzbeschreibung
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.
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Einleitungssatz
Statistics is fundamentally concerned with the understanding of structure in data. Lesen Sie die erste Seite
Buchdeckel | Copyright | Inhaltsverzeichnis | Auszug | Stichwortverzeichnis | Rückseite
Statistics is fundamentally concerned with the understanding of structure in data. Lesen Sie die erste Seite
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Buchdeckel | Copyright | Inhaltsverzeichnis | Auszug | Stichwortverzeichnis | Rückseite
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Kundenrezensionen
Die hilfreichsten Kundenrezensionen
3 von 7 Kunden fanden die folgende Rezension hilfreich
Format:Gebundene Ausgabe
The book tells you everything you must know about S or R.It covers most of the statistical methods used.It is very comfortable to read and can be used as reference.I just can recommend this book. It is a complete reference for studies and for practical statistics. I'm sure you find everything an average user needs to know about S or R in this book.
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48 von 48 Kunden fanden die folgende Rezension hilfreich
Excellent
6. März 2003
Format:Gebundene Ausgabe
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.
32 von 32 Kunden fanden die folgende Rezension hilfreich
R deserves the coverage it gets here
2. September 2004
Format:Gebundene Ausgabe|Von Amazon bestätigter Kauf
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.
25 von 25 Kunden fanden die folgende Rezension hilfreich
Book Contents
17. Dezember 2005
Format:Gebundene Ausgabe|Von Amazon bestätigter Kauf
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
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