A Computational Approach to Statistical Arguments in Ecology and Evolution

George F. Estabrook

doi:10.1017/CBO9780511783708

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Scientists need statistics. Increasingly this is accomplished using computational approaches. Freeing readers from the constraints, mysterious formulas and sophisticated mathematics of classical statistics, this book is ideal for researchers who want to take control of their own statistical arguments. It demonstrates how to use spreadsheet macros to calculate the probability distribution predicted for any statistic by any hypothesis. This enables readers to use anything that can be calculated (or observed) from their data as a test statistic and hypothesize any probabilistic mechanism that can generate data sets similar in structure to the one observed. A wide range of natural examples drawn from ecology, evolution, anthropology, palaeontology and related fields give valuable insights into the application of the described techniques, while complete example macros and useful procedures demonstrate the methods in action and provide starting points for readers to use or modify in their own research.

'I recommend this volume to students and researchers looking for an easy, interesting, and condensed introduction to a computational approach to statistics.'

Source: The Quarterly Review of Botany

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A Computational Approach to Statistical Arguments in Ecology and Evolution

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Contents

Frontmatter
pp i-iv

Contents
pp v-vi

Acknowledgments
pp vii-viii

1 - Introduction
pp 1-19

2 - Programming and statistical concepts
pp 20-58

3 - Choosing a test statistic
pp 59-76

4 - Random variables and distributions
pp 77-100

5 - More programming and statistical concepts
pp 101-121

6 - Parametric distributions
pp 122-140

7 - Linear model
pp 141-168

8 - Fitting distributions
pp 169-181

9 - Dependencies
pp 182-212

10 - How to get away with peeking at data
pp 213-219

11 - Contingency
pp 220-252

References
pp 253-255

Index
pp 256-257

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