### Introduction to Biometry

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 chos...

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Main Author: eBook English New York, NY Springer US 1999, 1999 1st ed. 1999 Springer Book Archives -2004 - Collection details see MPG.ReNa
• 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’st
• 7 The distribution of?2(chi squared)
• 8 The distribution of the variance ratio, F = S12/S12
• 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 indicesg1andg2
• 14 The lognormal distribution
• 15 Testing hypotheses concerning frequency tables using the X2 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 correlations 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’sT2
• 31 Principal components orprincipal axes
• 32 Fisher’s linear discriminant function
• 33 Multiple discriminant analysis
• 34 Canonical correlations
• 35 Growthcurves and other nonlinear relationships
• Appendices
• The statistical tables most frequently used in biometry
• The standardized normal distribution
• The distribution of x (chi squared)