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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