Ecological Models and Data in R Hardback - 2008 - 508th Edition
by Benjamin M. Bolker
- New
- Hardcover
Description
Standard delivery: 7 to 12 days
Details
- Title Ecological Models and Data in R
- Author Benjamin M. Bolker
- Binding Hardback
- Edition number 508th
- Edition 508
- Condition New
- Pages 408
- Volumes 1
- Language ENG
- Publisher Princeton University Press
- Date 2008-07-21
- Features Bibliography, Index, Table of Contents
- Bookseller's Inventory # ria9780691125220_inp
- ISBN 9780691125220 / 0691125228
- Weight 2.2 lbs (1.00 kg)
- Dimensions 10.1 x 7.1 x 1.1 in (25.65 x 18.03 x 2.79 cm)
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Themes
- Topical: Ecology
- Library of Congress subjects Ecology - Statistical methods, R (Computer program language)
- Library of Congress Catalog Number 2007060388
- Dewey Decimal Code 577.015
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From the publisher
From the rear cover
"This user-friendly introduction to likelihood and Bayesian statistical methods for ecology students is set apart by its emphasis on implementation in R. This alone will make it more useful than previous books. In contrast to other texts, Bolker's book explains how to fit models to data in enough detail that even students with little programming experience will be able to follow along. I expect this to become an exceedingly popular textbook."--Stephan B. Munch, Stony Brook University
"Benjamin Bolker is a pioneer in helping ecology students make the leap from a casual understanding of modern statistical methods to a hands-on application of these tools to their own precious data sets. This book shows the lessons learned from teaching this material to several cohorts of graduate students. No other book I've read gives such a good feel for the compromises scientists have to make in searching for good statistical models."--Brian Inouye, Florida State University
"I have no doubt that this book will become a fixture on many ecologists' bookshelves (it certainly will be on mine). With a presentation that is gentle and encouraging rather than jargon-filled and intimidating, it empowers ecologists to develop their own statistical procedures. I strongly recommend it."--Timothy Essington, University of Washington
