A Computational Approach to Statistical Arguments in Ecology and Evolution
Author:   George F. Estabrook (University of Michigan, Ann Arbor)
Publisher:   Cambridge University Press
Edition:   New edition
ISBN:  

9780511783708


Publication Date:   05 June 2012
Format:   Undefined
Availability:   Available To Order   Availability explained
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A Computational Approach to Statistical Arguments in Ecology and Evolution


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Author:   George F. Estabrook (University of Michigan, Ann Arbor)
Publisher:   Cambridge University Press
Imprint:   Cambridge University Press (Virtual Publishing)
Edition:   New edition
ISBN:  

9780511783708


ISBN 10:   0511783701
Publication Date:   05 June 2012
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Tertiary & Higher Education
Format:   Undefined
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

Table of Contents

Acknowledgements; 1. Introduction; 2. Programming and statistical concepts; 3. Choosing a test statistic; 4. Random variables and distributions; 5. More programming and statistical concepts; 6. Parametric distributions; 7. Linear model; 8. Fitting distributions; 9. Dependencies; 10. How to get away with peeking at data; 11. Contingency; References; Index.

Reviews

The book uses fascinating examples from diverse disciplines to illustrate the power and ease of this approach. The examples, along with clear, step-by-step programming instructions, are described in chapters on programming techniques, test statistics, random variables, resampling, parametric probability distributions, linear models, goodness of fit, and contingency. Keith Hunley & Jessica Gross, Journal of Anthropological Research


Author Information

George Estabrook is a Professor of Botany in the Department of Ecology and Evolutionary Biology at the University of Michigan, Ann Arbor. He is interested in the application of mathematics and computing to biology and has taught graduate courses on the subject for more than 30 years.

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