A Primer Of Ecological Statistics

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9780878932696: A Primer Of Ecological Statistics

A Primer of Ecological Statistics explains fundamental material in probability theory and experimental design for ecologists and environmental scientists. The book emphasizes a general introduction to probability theory and provides a detailed discussion of specific designs and analyses that are typically encountered in ecology and environmental science. Appropriate for use as either a stand-alone or supplementary text for upper-division undergraduate or graduate courses in ecological and environmental statistics, ecology, environmental science, environmental studies, or experimental design, the Primer also serves as a resource for environmental professionals who need to use and interpret statistics daily but have little or no formal training in the subject.

The book is divided into three parts. Part I discusses the fundamentals of probability and statistical thinking. It introduces the logic and language of probability (Chapter 1), explains common statistical distributions used in ecology (Chapter 2) and important measures of central tendency and spread (Chapter 3), explains P-values, hypothesis testing, and statistical errors (Chapter 4), and introduces frequentist, Bayesian, and Monte Carlo methods of analysis (Chapter 5).

Part II discusses how to successfully design and execute field experiments and sampling studies. Topics include design strategies (Chapter 6), a "bestiary" of experimental designs (Chapter 7), and transformations and data management (Chapter 8).

Part III discusses specific analyses, and covers the material that is the main core of most statistics texts. Topics include regression (Chapter 9), analysis of variance (Chapter 10), categorical data analysis (Chapter 11), and multivariate analysis (Chapter 12).

The book includes a comprehensive glossary, a mathematical appendix on matrix algebra, and extensively annotated tables and figures. Footnotes introduce advanced and ancillary material: some are purely historical, others cover mathematical/statistical proofs or details, and still others address current topics in the ecological literature.

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About the Author:

Nicholas J. Gotelli is Professor in the Department of Biology at the University of Vermont. He graduated with a B.A. from the University of California, Berkeley in 1980, and earned his Ph.D. at Florida State University in 1985. He is also the author of A Primer of Ecology, third edition (2001, Sinauer Associates, Inc.), Null Models in Ecology (with Gary R. Graves; 1996, Smithsonian Press), and EcoSim, an ecological software package. Dr. Gotelli currently serves on the Board of Editors of Ecology and Ecology Letters. His research interests include: the evolutionary ecology of carnivorous plants, biogeography, null model analysis of community structure, ant diversity, and demography. Aaron M. Ellison is Senior Research Fellow in Organismic and Evolutionary Biology at the Harvard Forest, and Adjunct Professor in the Graduate Program in Organismic and Evolutionary Biology at the University of Massachusetts at Amherst. He received a B.A. in 1982 from Yale University, and a Ph.D. from Brown University in 1986. Dr. Ellison received the National Science Foundation's Presidential Faculty Fellow award in 1992 for 'demonstrated excellence and continued promise both in scientific and engineering research and in teaching future generations of students to extend and apply human knowledge.' His research foci include: food web dynamics, community ecology of wetlands and forests, evolutionary ecology of carnivorous plants, and the application of Bayesian inference to ecological research and environmental decision-making. Dr. Ellison currently serves as Associate Editor-in-Chief of Ecology and Ecological Monographs, with primary responsibility for statistically oriented manuscripts

Review:

In short, only positive superlatives come to mind to describe the merit of this book. Its obvious strength is that is was written by ecologists for ecologists. From now on, I will use this textbook to teach statistics to undergraduate students and I will suggest it to graduate students and researchers who need to refresh their statistical knowledge. --Marie-Josée Fortin, Écoscience

This volume provides a wonderful review of traditional statistical methods. It is also an introduction to new statistical ideas. I highly recommend it. --Philip M. Dixon, The Quarterly Review of Biology

This volume provides a wonderful review of traditional statistical methods. It is also an introduction to new statistical ideas. I highly recommend it. --Philip M. Dixon, The Quarterly Review of Biology

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