R for Statistics

Author:   Pierre-Andre Cornillon (Universite Rennes 2, France) ,  Arnaud Guyader (Universite Rennes 2, France) ,  Francois Husson (AGROCAMPUS OUEST, Rennes, France) ,  Nicolas Jegou (Universite Rennes 2, France)
Publisher:   Taylor & Francis Inc
ISBN:  

9781439881453


Pages:   320
Publication Date:   21 March 2012
Format:   Paperback
Availability:   In Print   Availability explained
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R for Statistics


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Overview

This text explores the use of R for classical statistical analysis. The first half of the book introduces R, data manipulation and visualization, statistical models, graphics, and R programming. The second half presents various statistical analysis techniques by first introducing the data example, then describing the problem to solve, and finally conducting the analysis using R. This example-based approach enables readers to replicate the analyses using their own data. Some of the techniques covered include simple regression, multiple regression, ANOVA, logistic regression, principal component analysis, and clustering.

Full Product Details

Author:   Pierre-Andre Cornillon (Universite Rennes 2, France) ,  Arnaud Guyader (Universite Rennes 2, France) ,  Francois Husson (AGROCAMPUS OUEST, Rennes, France) ,  Nicolas Jegou (Universite Rennes 2, France)
Publisher:   Taylor & Francis Inc
Imprint:   Chapman & Hall/CRC
Dimensions:   Width: 15.60cm , Height: 2.00cm , Length: 23.40cm
Weight:   1.050kg
ISBN:  

9781439881453


ISBN 10:   1439881456
Pages:   320
Publication Date:   21 March 2012
Audience:   College/higher education ,  General/trade ,  Tertiary & Higher Education ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

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.

Reviews

[T]he book is accessible for statisticians of all levels and areas of expertise as well as for novice and advanced R users. ... I recommend it for anyone who wants to learn about the why and how of the most commonly employed statistical methods and their extensions. -Irina Kukuyeva, Journal of Statistical Software, Vol. 51, November 2012


Author Information

Pierre-Andre Cornillon, Arnaud Guyader, Francois Husson, Nicolas Jegou, Julie Josse, Maela Kloareg, ric Matzner-Lober, Laurent Rouvière

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