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Preface | p. xiii |
Notes on the Fourth Edition | p. xvii |
Introduction | p. 1 |
Some Definitions | p. 1 |
The Development of Biometry | p. 3 |
The Statistical Frame of Mind | p. 5 |
Data in Biology | p. 9 |
Samples and Populations | p. 9 |
Variables in Biology | p. 11 |
Accuracy and Precision of Data | p. 13 |
Derived Variables | p. 16 |
Frequency Distributions | p. 19 |
Computers and Data Analysis | p. 33 |
Computers | p. 33 |
Software | p. 35 |
Efficiency and Economy in Data Processing | p. 37 |
Descriptive Statistics | p. 39 |
The Arithmetic Mean | p. 40 |
Other Means | p. 44 |
The Median | p. 45 |
The Mode | p. 47 |
Sample Statistics and Parameters | p. 49 |
The Range | p. 49 |
The Standard Deviation | p. 51 |
Coding Data Before Computation | p. 54 |
The Coefficient of Variation | p. 55 |
Introduction to Probability Distributions: Binomial and Poisson | p. 59 |
Probability, Random Sampling, and Hypothesis Testing | p. 60 |
The Binomial Distribution | p. 68 |
The Poisson Distribution | p. 78 |
Other Discrete Probability Distributions | p. 87 |
The Normal Probability Distribution | p. 93 |
Frequency Distributions of Continuous Variables | p. 93 |
Properties of the Normal Distribution | p. 95 |
A Model for the Normal Distribution | p. 100 |
Applications of the Normal Distribution | p. 102 |
Fitting a Normal Distribution to Observed Data | p. 104 |
Skewness and Kurtosis | p. 106 |
Graphic Methods | p. 108 |
Other Continuous Distributions | p. 117 |
Hypothesis Testing and Interval Estimation | p. 119 |
Introduction to Hypothesis Testing: Randomization Approaches | p. 120 |
Distribution and Variance of Means | p. 131 |
Distribution and Variance of Other Statistics | p. 137 |
The t-Distribution | p. 140 |
More on Hypothesis Testing: Normally Distributed Data | p. 142 |
Power of a Test | p. 146 |
Tests of Simple Hypotheses Using the Normal and f-Distributions | p. 148 |
The Chi-Square Distribution | p. 154 |
Testing the Hypothesis H_{0}: ¿^{2} = ¿^{2}_{0} | p. 156 |
Introduction to Interval Estimation (Confidence Limits) | p. 157 |
Confidence Limits Using Sample Standard Deviations | p. 162 |
Confidence Limits for Variances | p. 167 |
The Jackknife and the Bootstrap | p. 168 |
Introduction to Analysis of Variance | p. 177 |
Variances of Samples and Their Means | p. 178 |
TheF-Distribution | p. 182 |
The Hypothesis H_{0}: ¿^{2}_{1} = ¿^{2}_{2} | p. 187 |
Heterogeneity Among Sample Means | p. 190 |
Partitioning the Total Sum of Squares and Degrees of Freedom | p. 197 |
Model I Anova | p. 200 |
Model II Anova | p. 203 |
Single-Classification Analysis of Variance | p. 207 |
Computational Formulas | p. 208 |
General Case: Unequal and Equal n | p. 208 |
Special Case: Two Groups | p. 220 |
Comparisons Among Means in a Model I Anova: Essential Background | p. 228 |
Comparisons Among Means: Special Methods | p. 246 |
Nested Analysis of Variance | p. 277 |
Nested Anova: Design | p. 277 |
Nested Anova: Computation | p. 280 |
Nested Anovas with Unequal Sample Sizes | p. 301 |
Two-Way and Multiway Analysis of Variance | p. 319 |
Two-Way Anova: Design | p. 319 |
Two-Way Anova with Equal Replication: Computation | p. 321 |
Two-Way Anova: Hypothesis Testing | p. 331 |
Two-Way Anova Without Replication | p. 340 |
Paired Comparisons | p. 349 |
The Factorial Design | p. 354 |
A Three-Way Factorial Design | p. 355 |
Higher-Order Factorial Anovas | p. 365 |
Other Designs | p. 370 |
Anova by Computer | p. 372 |
Statistical Power and Sample Size in the Analysis of Variance | p. 379 |
Effect Size | p. 379 |
Noncentral t- and F-Distributions and Confidence Limits for Effect Sizes | p. 382 |
Power in an Anova | p. 390 |
Sample Size in an Anova | p. 391 |
Minimum Detectable Difference | p. 395 |
Post Hoc Power Analysis | p. 396 |
Optimal Allocation of Resources in a Nested Design | p. 397 |
Randomized Blocks and Other Two-Way and Multiway Designs | p. 406 |
Assumptions of Analysis of Variance | p. 409 |
A Fundamental Assumption | p. 410 |
Independence | p. 410 |
Homogeneity of Variances | p. 413 |
Normality | p. 422 |
Transformations | p. 426 |
The Logarithmic Transformation | p. 427 |
The Square Root Transformation | p. 433 |
The Box-Cox Transformation | p. 435 |
The Arcsine Transformation | p. 438 |
Nonparametric Methods in Lieu of Single-Classification Anova | p. 440 |
Nonparametric Methods in Lieu of Two-Way Anova | p. 460 |
Linear Regression | p. 471 |
Introduction to Regression | p. 472 |
Models in Regression | p. 475 |
The Linear Regression Equation | p. 477 |
Hypothesis Testing in Regression | p. 485 |
More Than One Value of Y for Each Value of X | p. 495 |
The Uses of Regression | p. 506 |
Estimating X From Y | p. 511 |
Comparing Two Regression Lines | p. 513 |
Linear Comparisons in Anovas | p. 515 |
Examining Residuals and Transformations in Regression | p. 524 |
Nonparametric Tests for Regression | p. 532 |
Model II Regression | p. 535 |
Effect Size, Power, and Sample Size in Regression | p. 544 |
Correlation | p. 551 |
Correlation Versus Regression | p. 551 |
The Product-Moment Correlation Coefficient | p. 554 |
Computing the Product-Moment Correlation Coefficient | p. 562 |
The Variance of Sums and Differences | p. 565 |
Hypothesis Tests for Correlations | p. 567 |
Applications of Correlation | p. 577 |
Nonparametric Tests for Association | p. 580 |
Major Axes and Confidence Regions | p. 588 |
Effect Size, Power, and Sample Size | p. 592 |
Multiple and Curvilinear Regression | p. 603 |
Multiple Regression: Computation | p. 604 |
Multiple Regression: Hypothesis Tests | p. 614 |
Path Analysis and Structural Equation Modeling | p. 625 |
Partial and Multiple Correlation | p. 644 |
Selection of Independent Variables | p. 649 |
Computation of Multiple Regression by Matrix Methods | p. 656 |
Solving Anovas as Regression Problems: General Linear Models | p. 659 |
Analysis of Covariance (Ancova) | p. 665 |
Curvilinear Regression | p. 671 |
Effect Size, Power, and Sample Size in Multiple Regression | p. 685 |
Advanced Topics in Regression and Correlation | p. 694 |
Analysis of Frequencies | p. 703 |
Introduction to Tests for Goodness of Fit | p. 704 |
Single-Classification Tests for Goodness of Fit | p. 714 |
Replicated Tests of Goodness of Fit | p. 730 |
Tests of Independence: Two-Way Tables | p. 739 |
Analysis of Three-Way Tables | p. 758 |
Analysis of Proportions | p. 773 |
Randomized Blocks for Frequency Data | p. 793 |
Effect Sizes, Power, and Sample Sizes | p. 801 |
Meta-Analysis and Miscellaneous Methods | p. 817 |
Synthesis of Prior Research Results: Meta-Analysis | p. 817 |
Tests for Randomness of Nominal Data: Runs Tests | p. 841 |
Isotonic Regression | p. 847 |
Application of Randomization Tests to Unconventional Statistics | p. 850 |
The Mantel Test of Association Between Two Distance Matrices | p. 852 |
The Future of Biometry: Data Analysis | p. 859 |
Appendices | |
Mathematical Proofs | p. 869 |
Introduction to Matrices | p. 885 |
Bibliography | p. 891 |
Author Index | p. 909 |
Subject Index | p. 915 |
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