Synopses & Reviews
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.
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
Synopsis
Includes bibliographical references (p. [346]-351) and indexes.
Synopsis
The R system is a powerful statistics system for researchers needing tools for data manipulation and presentation. Concentrating on examples drawn from the authors' teaching and consulting experience, this book is both a tutorial to the R system and an introduction to the underlying statistical methods. Starting with elementary concepts accessible to anyone who has taken a first undergraduate course in statistics the book leads on to more advanced topics of use to practising scientists and researchers as well as students in medicine, science, engineering and the social sciences.
Synopsis
Extensive examples illustrate the use of R, a statistical computing environment, and the modern statistical methods that can be used with it. Starting with elementary concepts, the authors proceed to introduce advanced topics of use to researchers or students in medicine, science, engineering and the social sciences. R code and data sets for all examples will be available on the Web.
Synopsis
Text explaining basic statistical methods in the R programming language through extensive use of examples.
Table of Contents
Introduction; 1. A brief introduction to R; 2. Styles of data analysis; 3. Statistical models; 4. Introduction to formal inference; 5. Regression with a single predictor; 6. Multiple linear regression; 7. Exploiting the linear model framework; 8. Logistic regression and other generalised linear models; 9. Multi-level models, time series and repeated measures; 10. Tree-based classification and regression; 11. Multivariate data exploration and discrimination; 12. The R system - additional topics; 13. Epilogue - models; Appendix: S-plus differences; Bibliography; Acknowledgements; Index.