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Introduction. 1. Looking at Quantitative Biological Data Through Scatter Diagrams. 2. Samples and Populations, Estimates and Parameters. 3. Frequencies and Probabilities. 4. Measures of Central Tendency and of Dispersion. 5. The Normal Distribution. 6. The Distribution of Student's t. 7. The Distribution of chi2 (chi squared). 8. The Distribution of the Variance Ratio, F = S21/S22. 9. Hypotheses and Confidence Intervals Concerning One or Two Means. 10. Hypotheses and Confidence Intervals Concerning One Variance. 11. Hypotheses and Confidence Intervals Concerning a Variance Ratio. 12. The Analysis of Variance or `ANOVA' (One-Way, Type I). 13. The Skewness and Peakedness Indices, g1 and g2. 14. The Lognormal Distribution. 15. Testing Hypotheses Concerning Frequency Tables Using the chi2 Distribution. 16. Tests of Goodness of Fit. 17. The Binomial Distribution. 18. The Poisson Distribution. 19. The Bivariate Normal Distribution and the Correlation Coefficient, r. 20. Estimation Lines (the So-Called `Regression' Lines). 21. The Analysis of Covariance or `ANCOVA': Comparing Estimation Lines. 22. The Orthogonal Estimation Line or major axis. 23. The Trivariate Normal Distribution: Partial and Multiple Correlations and Regressions. 24. Elementary Linear Calculations (Vectors and Matrices). 25. Partial and Multiple Correlatons and Regressions: Matrix Calculations. 26. One-Way Type I Analysis of Variance with Contrasts. 27. One-Way Type II Analysis of Variance with Variance Components. 28. Two-Way Type I Analysis of Variance with Interaction. 29. The Multivariate Normal Distribution. 30. The Distribution of Hotelling's T2. 31. Principal Components or principal axes. 32. Fisher's Linear Discriminant Function. 33. Multiple Discriminant Analysis. 34. Canonical Correlations. 35. Growth Curves and Other Nonlinear Relationships. Appendices. Bibliography. The Statistical Tables Most Frequently Used in Biometry. Author Index. Subject Index.

Statistical methods are becoming more important in all biological fields of study. Biometry deals with the application of mathematical techniques to the quantitative study of varying characteristics of organisms, populations, species, etc. This book uses examples based on genuine data carefully chosen by the author for their special biological significance. The chapters cover a broad spectrum of topics and bridge the gap between introductory biological statistics and advanced approaches such as multivariate techniques and nonlinear models. A set of statistical tables most frequently used in biometry completes the book.