Data Analysis and Graphics Using R: An Example-based Approach (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 10)

Maindonald, John

ISBN 10: 0521861160 / ISBN 13: 9780521861168

Published by Cambridge University Press, 2006

About this Item

Most items will be dispatched the same or the next working day. A copy that has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Seller Inventory # wbs9179322302

Bibliographic Details

• Title: Data Analysis and Graphics Using R: An Example-based Approach (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 10)
• Publisher: Cambridge University Press
• Publication Date: 2006
• Language: English
• ISBN 10: 0521861160
• ISBN 13: 9780521861168
• Binding: Hardcover
• Edition: 2nd Edition
• Condition: Very Good
• Weight: 1090 grams

About this title

Synopsis

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.

About the Authors

John Maindonald is Visiting Fellow at the Mathematical Sciences Institute, Australian National University. He has collaborated extensively with scientists in a wide range of application areas, from medicine and public health, to population genetics, machine learning, economic history, and forensic linguistics.

John Braun is Associate Professor of Statistical and Actuarial Sciences, University of Western Ontario. He has collaborated with biostatisticians, biologists, psychologists and most recently has become involved with a network of forestry researchers.