Data analysis and graphics using R

An example-based approach

John Maindonald, John Braun

386 pages, parution le 15/10/2003

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Résumé

Modern statistical software systems provide sophisticated tools for researchers who need to manipulate and display their data. Using such systems requires training both in the software itself and in the statistical methods that it relies on. Concentrating on the freely available R system, this book demonstrates recently implemented approaches and methods in statistical analysis. The authors introduce elementary concepts in statistics through examples of real-world data analysis drawn from the authors' experience, both as teachers and as consultants.

R code and data sets for all examples are available on the Internet. This emphasis on practical methodology combined with a tutorial approach makes the book accessible to anyone with a knowledge of undergraduate-level statistics, whether a research student or a practising scientist or statistician. The methods demonstrated are suitable for use in a wide variety of disciplines, from social sciences to medicine, engineering and science.

Introduction
A brief introduction to R
Styles of data analysis
Statistical models
Introduction to formal inference
Regression with a single predictor
Multiple linear regression
Exploiting the linear model framework
Logistic regression and other generalised linear models
Multi-level models, time series and repeated measures
Tree-based classification and regression
Multivariate data exploration and discrimination
The R system - additional topics
Epilogue - models
Appendix
References
Index of R symbols and functions
Index of names
Index of terms

Caractéristiques techniques

	PAPIER
Éditeur(s)	Cambridge University Press
Auteur(s)	John Maindonald, John Braun
Parution	15/10/2003
Nb. de pages	386
Format	18 x 26
Couverture	Relié
Poids	845g
Intérieur	Noir et Blanc
EAN13	9780521813365