A Computational Approach to Statistical Arguments in Ecology and Evolution
eBook - PDF

A Computational Approach to Statistical Arguments in Ecology and Evolution

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

A Computational Approach to Statistical Arguments in Ecology and Evolution

About this book

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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Yes, you can access A Computational Approach to Statistical Arguments in Ecology and Evolution by George F. Estabrook in PDF and/or ePUB format, as well as other popular books in Medicine & Biostatistics. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. Title
  3. Copyright
  4. Contents
  5. Acknowledgments
  6. 1 Introduction
  7. 2 Programming and statistical concepts
  8. 3 Choosing a test statistic
  9. 4 Random variables and distributions
  10. 5 More programming and statistical concepts
  11. 6 Parametric distributions
  12. 7 Linear model
  13. 8 Fitting distributions
  14. 9 Dependencies
  15. 10 How to get away with peeking at data
  16. 11 Contingency
  17. References
  18. Index