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A Computational Approach to Statistical Arguments in Ecology and Evolution

Autor George F. Estabrook
en Limba Engleză Hardback – 28 sep 2011
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.
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Specificații

ISBN-13: 9781107004306
ISBN-10: 1107004306
Pagini: 266
Ilustrații: 4 b/w illus.
Dimensiuni: 157 x 235 x 17 mm
Greutate: 0.54 kg
Ediția:Nouă
Editura: Cambridge University Press
Colecția Cambridge University Press
Locul publicării:New York, United States

Cuprins

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.

Recenzii

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

Notă biografică


Descriere

This book teaches powerful methods to test hypotheses using statistical arguments without the constraints and sophisticated mathematics of classical statistics.