A Primer of Ecological Statistics
Language: English
Published by Oxford University Press, OUP USA, 2012
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 308.05
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Add to basketItem description from seller
Neuware - Published by Sinauer Associates, an imprint of Oxford University Press. A Primer of Ecological Statistics, Second Edition, explains fundamental material in probability theory, experimental design, and parameter estimation 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 four 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).Part IV--new to this edition--discusses two central topics in estimating important ecological metrics. Topics include quantification of biological diversity (Chapter 13) and estimating occupancy, detection probability, and population sizes from marked and unmarked populations (Chapter 14).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.…
Seller Inventory # 9781605350646
- Title
- A Primer of Ecological Statistics
- Author
- Nicholas J. Gotelli
- Publisher
- Oxford University Press, OUP USA
- Publication year
- 2012
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1605350648
- ISBN 13
- 9781605350646
- Edition
- 2nd Edition
- Item weight
- 992 grams
- Dimensions
- 236x177x25 mm
"Synopsis" may belong to another edition of this title.
About the Author
Aaron M. Ellison is Senior Research Fellow in Ecology 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." He is also the author of A Field Guide to the Ants of New England (with Nicholas J. Gotelli, Elizabeth J. Farnsworth, and Gary D. Alpert; 2012). 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.
"About the title" may belong to another edition of this title.
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