R for Statistics
Seiten
2012
Chapman & Hall/CRC (Verlag)
978-1-4398-8145-3 (ISBN)
Chapman & Hall/CRC (Verlag)
978-1-4398-8145-3 (ISBN)
Although there are currently a wide variety of software packages suitable for the modern statistician, R has the triple advantage of being comprehensive, widespread, and free. Published in 2008, the second edition of Statistiques avec R enjoyed great success as an R guidebook in the French-speaking world. Translated and updated, R for Statistics includes a number of expanded and additional worked examples.
Organized into two sections, the book focuses first on the R software, then on the implementation of traditional statistical methods with R.
Focusing on the R software, the first section covers:
Basic elements of the R software and data processing
Clear, concise visualization of results, using simple and complex graphs
Programming basics: pre-defined and user-created functions
The second section of the book presents R methods for a wide range of traditional statistical data processing techniques, including:
Regression methods
Analyses of variance and covariance
Classification methods
Exploratory multivariate analysis
Clustering methods
Hypothesis tests
After a short presentation of the method, the book explicitly details the R command lines and gives commented results. Accessible to novices and experts alike, R for Statistics is a clear and enjoyable resource for any scientist.
Datasets and all the results described in this book are available on the book’s webpage at http://www.agrocampus-ouest.fr/math/RforStat
Organized into two sections, the book focuses first on the R software, then on the implementation of traditional statistical methods with R.
Focusing on the R software, the first section covers:
Basic elements of the R software and data processing
Clear, concise visualization of results, using simple and complex graphs
Programming basics: pre-defined and user-created functions
The second section of the book presents R methods for a wide range of traditional statistical data processing techniques, including:
Regression methods
Analyses of variance and covariance
Classification methods
Exploratory multivariate analysis
Clustering methods
Hypothesis tests
After a short presentation of the method, the book explicitly details the R command lines and gives commented results. Accessible to novices and experts alike, R for Statistics is a clear and enjoyable resource for any scientist.
Datasets and all the results described in this book are available on the book’s webpage at http://www.agrocampus-ouest.fr/math/RforStat
Pierre-Andre Cornillon, Arnaud Guyader, Francois Husson, Nicolas Jegou, Julie Josse, Maela Kloareg, ric Matzner-Lober, Laurent Rouvière
An Overview of R: Main Concepts. Preparing Data. R Graphics. Making Programs with R. Statistical Methods: Introduction to the Statistical Methods. A Quick Start with RHypothesis Test. Regression. Analysis of Variance and Covariance. ClassificationExploratory Multivariate Analysis. Clustering. Appendix.
| Erscheint lt. Verlag | 20.4.2012 |
|---|---|
| Zusatzinfo | 8 Tables, black and white; 89 Illustrations, black and white |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 1050 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Computerprogramme / Computeralgebra |
| Mathematik / Informatik ► Mathematik ► Statistik | |
| ISBN-10 | 1-4398-8145-6 / 1439881456 |
| ISBN-13 | 978-1-4398-8145-3 / 9781439881453 |
| Zustand | Neuware |
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