Ecological Statistics: Contemporary theory and application by Gordon A. Fox

Ecological Statistics: Contemporary theory and application

EditorGordon A. Fox, Simoneta Negrete-Yankelevich, Vinicio J. Sosa

Paperback | February 18, 2015

not yet rated|write a review

Pricing and Purchase Info

$80.39 online 
$81.95 list price
Earn 402 plum® points
HURRY, ONLY 1 LEFT!

In stock online

Ships free on orders over $25

Not available in stores

about

The application and interpretation of statistics are central to ecological study and practice. Ecologists are now asking more sophisticated questions than in the past. These new questions, together with the continued growth of computing power and the availability of new software, have createda new generation of statistical techniques. These have resulted in major recent developments in both our understanding and practice of ecological statistics. This novel book synthesizes a number of these changes, addressing key approaches and issues that tend to be overlooked in other books such as missing/censored data, correlation structure of data, heterogeneous data, and complex causal relationships. These issues characterize a large proportion ofecological data, but most ecologists' training in traditional statistics simply does not provide them with adequate preparation to handle the associated challenges. Uniquely, Ecological Statistics highlights the underlying links among many statistical approaches that attempt to tackle these issues.In particular, it gives readers an introduction to approaches to inference, likelihoods, generalized linear (mixed) models, spatially or phylogenetically-structured data, and data synthesis, with a strong emphasis on conceptual understanding and subsequent application to data analysis. Written by a team of practicing ecologists, mathematical explanations have been kept to the minimum necessary. This user-friendly textbook will be suitable for graduate students, researchers, and practitioners in the fields of ecology, evolution, environmental studies, and computational biology whoare interested in updating their statistical tool kits. A companion web site provides example data sets and commented code in the R language.

About The Author

Gordon Fox received his Ph.D. from the University of Arizona and was a postdoctoral fellow at the University of California, Davis. He is currently Associate Professor in the Department of Integrative Biology at the University of South Florida. His research involves theoretical issues in ecology and population biology, and empirical stu...

Details & Specs

Title:Ecological Statistics: Contemporary theory and applicationFormat:PaperbackDimensions:416 pages, 9.69 × 7.44 × 0.81 inPublished:February 18, 2015Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0199672555

ISBN - 13:9780199672554

Look for similar items by category:

Customer Reviews of Ecological Statistics: Contemporary theory and application

Reviews

Extra Content

Table of Contents

Vinicio J. Sosa, Simoneta Negrete-Yankelevich, and Gordon A. Fox: Introduction1. Michael A. McCarthy: Approaches to Statistical Inference2. Earl D. McCoy: Having the Right Stuff: the Effects of Data Constraints on Ecological Data Analysis3. Shane A. Richards: Likelihood and Model Selection4. Shinichi Nakagawa: Missing Data: Mechanisms, Methods and Messages5. Gordon A. Fox: What You Don't Know Can Hurt You: Censored and Truncated Data in Ecological Research6. Yvonne M. Buckley: Generalized Linear Models7. Bruce E. Kendall: A Statistical Symphony: Instrumental Variables Reveal Causality and Control Measurement Error8. James B. Grace, Samuel M. Scheiner, and Donald R. Schoolmaster, Jr.: Structural Equation Modeling: Building and Evaluating Causal Models9. Jessica Gurevitch and Shinichi Nakagawa: Research Synthesis Methods in Ecology10. Simoneta Negrete-Yankelevich and Gordon A. Fox: Spatial Variation and Linear Modeling of Ecological Data11. Marc J. Lajeunesse and Gordon A. Fox: Statistical Approaches to the Problem of Phylogenetically Correlated Data12. Jonathan R. Rhodes: Mixture Models for Overdispersed Data13. Benjamin M. Bolker: Linear and Generalized Linear Mixed ModelsAppendix