Synopses & Reviews
Join the revolution ignited by the ground-breaking R system! Starting with an introduction to R, covering standard regression methods, then presenting more advanced topics, this book guides users through the practical and powerful tools that the R system provides. The emphasis is on hands-on analysis, graphical display and interpretation of data. The many worked examples, taken from real-world research, are accompanied by commentary on what is done and why. A website provides computer code and data sets, allowing readers to reproduce all analyses. Updates and solutions to selected exercises are also available. Assuming only basic statistical knowledge, the book is ideal for research scientists, final-year undergraduate or graduate level students of applied statistics, and practising statisticians. It is both for learning and for reference. This revised edition reflects changes in R since 2003 and has new material on survival analysis, random coefficient models, and the handling of high-dimensional data.
Review
'\"The text includes a wealth of practical examples, drawn from a variety of practical applications which should be easily understood by the reader. The methods demonstrated are suitable for use in areas such as biology, social science, medicine and engineering. The core of the book is taken up with detailed discussion of regression methods which leads onto more advanced statistical concepts.\" ISI Short Book Reviews\"I would strongly recommend the book to scientists who have already had a regression or a linear models course who wish to learn to use R.\" R News'
Review
From reviews of previous edition: "The strength of the book is in the extensive examples of practical data analysis with complete examples of the R code necessary to carry out the analyses ... I would strongly recommend the book to scientists who have already had a regression or a linear models course and who wish to learn to use R ... I give it a strong recommendation to the scientist or data analyst who wishes to an easy-to-read and an understandable reference on the use of R for practical data analysis."
R NewsFrom reviews of previous edition: "The text includes a wealth of practical examples, drawn from a variety of practical applications which should be easily understood by the reader. The methods demonstrated are suitable for use in areas such as biology, social science, medicine and engineering. The core of the book is taken up with detailed discussion of regression methods which leads onto more advanced statistical concepts."
ISI Short Book ReviewsFrom reviews of previous edition: "This book does an excellent job of describing the basics of a variety of statistical tools, both classical and modern, through examples from a wide variety of disciplines ... the book's writing style is very readable, with clear explanations and precise introductions of all topics and terminology ... the book also provides a wealth of examples from various physical and social sciences, engineering, and medicine that have been effectively chosen to illustrate not only the basics of the statistical methods, but also some of the interesting subtleties of the analyses that may require careful interpretation and discussion ... I believe that they have ... created a readable book that is rich with clear explanations and illustrative examples of the capability of a diverse set of tools. The packaging of the material with the R language is natural, and the extensive web page of resources complements the book's usefulness for a road audience of statisticians and practitioners."
Biometrics
Synopsis
Using modern statistical software systems requires training both in the software itself and in the underlying statistical methods. Concentrating on the freely available R system, this volume 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 their experience 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. The methods demonstrated are suitable for use in a wide variety of disciplines, from social sciences to medicine, engineering and science.
Synopsis
This book guides users through the practical and powerful tools that the R system provides. The emphasis is on hands-on analysis, graphical display and interpretation of data. The many worked examples, taken from real-world research, are accompanied by commentary on what is done and why. A website provides computer code and data sets, allowing readers to reproduce all analyses. Updates and solutions to selected exercises are also available. Both for learning and for reference, ideal for research scientists, final-year undergraduate or graduate level students of applied statistics, and practising statisticians.
Synopsis
Text explaining basic statistical methods in the R programming language through extensive use of examples.
Synopsis
Hands-on guide to the R system for data analysis for scientists, students and practising statisticians.
Table of Contents
Preface; 1. A brief introduction to R; 2. Styles of data analysis; 3. Statistical models; 4. An introduction to formal inference; 5. Regression with a single predictor; 6. Multiple linear regression; 7. Exploiting the linear model framework; 8. Generalized linear models and survival analysis; 9. Time series models; 10. Multi-level models and repeated measures; 11. Tree-based classification and regression; 12. Multivariate data exploration and discrimination; 13. Regression on principal component or discriminant scores; 14. The R system - additional topics; Epilogue - models; References; Index of R symbols and functions; Index of terms; Index of names.