Biometry: The Principles and Practices of Statistics in Biological Research - Rilegato

Sokal, Robert R.; Rohlf, F. James

 
9780716786047: Biometry: The Principles and Practices of Statistics in Biological Research

Sinossi

This easily understood but rigorous introduction to biological statistics is a standard text and valuable reference for anyone doing scientific research. The fourth edition has been thoroughly revised and updated using computer calculations and the authors have expanded on important modern topics.

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L'autore

Robert R. Sokal is a Distinguished Professor Emeritus at Stony Brook University.  A native of Vienna, Austria, he attended college in Shanghai, China, and obtained his Ph.D. from the University of Chicago.  In both his research, which has ranged over a diverse group of topics, and his teaching, which spans almost a half-century, Dr. Sokal has always promoted the use of statistics in biology.  He is a fellow of the American Academy of Arts and Sciences and of the American Association for the Advancement of Science, and has been awarded the Charles Darwin Lifetime Achievement Award in Physical Anthropology.
 
F. James Rohlf is the John S. Toll Professor at Stony Brook University and a member of the New York Consortium in Evolutionary Primatology. He received his Ph.D. degree from the University of Kansas in 1962. Dr. Rohlf's research has focused on the development and interpretation of multivariate methods in biology, and he has extensive teaching experience in multivariate statistics, geometric morphometrics, and graduate-level biometry.

Contenuti

1. Introduction
2. Data in Biology
3. Computers and Data Analysis
4. Descriptive Statistics
5. Introduction to Probability Distributions: Binomial and Poisson
6. The Normal Probability Distribution
7. Hypothesis Testing and Interval Estimation
8. Introduction to Analysis of Variance
9. Single-Classification Analysis of Variance
10. Nested Analysis of Variance
11. Two-Way and Multiway Analysis of Variance
12. Statistical Power and Sample Size in the Analysis of Variance
13. Assumptions of Analysis of Variance
14. Linear Regression
15. Correlation
16. Multiple and Curvilinear Regression
17. Analysis of Frequencies
18. Meta-Analysis and Miscellaneous Methods
Mathematical Appendix

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