ISBN-10: 0716786044

ISBN-13: 9780716786047

Edition: 4th 2012 (Revised)

List price: $190.99
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Description: This introduction to biological statistics is a standard text and valuable reference for anyone doing scientific research. The fourth edition has been thoroughly revised an updated using computer calculations and the authors have expanded on important modern topics.

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Book details

List price: $190.99
Edition: 4th
Copyright year: 2012
Publisher: W. H. Freeman & Company
Publication date: 9/16/2011
Binding: Hardcover
Pages: 937
Size: 6.50" wide x 9.50" long x 2.00" tall
Weight: 3.256

Notes on the Fourth Edition
Some Definitions
The Development of Biometry
The Statistical Frame of Mind
Data in Biology
Samples and Populations
Variables in Biology
Accuracy and Precision of Data
Derived Variables
Frequency Distributions
Computers and Data Analysis
Efficiency and Economy in Data Processing
Descriptive Statistics
The Arithmetic Mean
Other Means
The Median
The Mode
Sample Statistics and Parameters
The Range
The Standard Deviation
Coding Data Before Computation
The Coefficient of Variation
Introduction to Probability Distributions: Binomial and Poisson
Probability, Random Sampling, and Hypothesis Testing
The Binomial Distribution
The Poisson Distribution
Other Discrete Probability Distributions
The Normal Probability Distribution
Frequency Distributions of Continuous Variables
Properties of the Normal Distribution
A Model for the Normal Distribution
Applications of the Normal Distribution
Fitting a Normal Distribution to Observed Data
Skewness and Kurtosis
Graphic Methods
Other Continuous Distributions
Hypothesis Testing and Interval Estimation
Introduction to Hypothesis Testing: Randomization Approaches
Distribution and Variance of Means
Distribution and Variance of Other Statistics
The t-Distribution
More on Hypothesis Testing: Normally Distributed Data
Power of a Test
Tests of Simple Hypotheses Using the Normal and f-Distributions
The Chi-Square Distribution
Testing the Hypothesis H<sub>0</sub>: �<sup>2</sup> = �<sup>2</sup><sub>0</sub>
Introduction to Interval Estimation (Confidence Limits)
Confidence Limits Using Sample Standard Deviations
Confidence Limits for Variances
The Jackknife and the Bootstrap
Introduction to Analysis of Variance
Variances of Samples and Their Means
The Hypothesis H<sub>0</sub>: �<sup>2</sup><sub>1</sub> = �<sup>2</sup><sub>2</sub>
Heterogeneity Among Sample Means
Partitioning the Total Sum of Squares and Degrees of Freedom
Model I Anova
Model II Anova
Single-Classification Analysis of Variance
Computational Formulas
General Case: Unequal and Equal n
Special Case: Two Groups
Comparisons Among Means in a Model I Anova: Essential Background
Comparisons Among Means: Special Methods
Nested Analysis of Variance
Nested Anova: Design
Nested Anova: Computation
Nested Anovas with Unequal Sample Sizes
Two-Way and Multiway Analysis of Variance
Two-Way Anova: Design
Two-Way Anova with Equal Replication: Computation
Two-Way Anova: Hypothesis Testing
Two-Way Anova Without Replication
Paired Comparisons
The Factorial Design
A Three-Way Factorial Design
Higher-Order Factorial Anovas
Other Designs
Anova by Computer
Statistical Power and Sample Size in the Analysis of Variance
Effect Size
Noncentral t- and F-Distributions and Confidence Limits for Effect Sizes
Power in an Anova
Sample Size in an Anova
Minimum Detectable Difference
Post Hoc Power Analysis
Optimal Allocation of Resources in a Nested Design
Randomized Blocks and Other Two-Way and Multiway Designs
Assumptions of Analysis of Variance
A Fundamental Assumption
Homogeneity of Variances
The Logarithmic Transformation
The Square Root Transformation
The Box-Cox Transformation
The Arcsine Transformation
Nonparametric Methods in Lieu of Single-Classification Anova
Nonparametric Methods in Lieu of Two-Way Anova
Linear Regression
Introduction to Regression
Models in Regression
The Linear Regression Equation
Hypothesis Testing in Regression
More Than One Value of Y for Each Value of X
The Uses of Regression
Estimating X From Y
Comparing Two Regression Lines
Linear Comparisons in Anovas
Examining Residuals and Transformations in Regression
Nonparametric Tests for Regression
Model II Regression
Effect Size, Power, and Sample Size in Regression
Correlation Versus Regression
The Product-Moment Correlation Coefficient
Computing the Product-Moment Correlation Coefficient
The Variance of Sums and Differences
Hypothesis Tests for Correlations
Applications of Correlation
Nonparametric Tests for Association
Major Axes and Confidence Regions
Effect Size, Power, and Sample Size
Multiple and Curvilinear Regression
Multiple Regression: Computation
Multiple Regression: Hypothesis Tests
Path Analysis and Structural Equation Modeling
Partial and Multiple Correlation
Selection of Independent Variables
Computation of Multiple Regression by Matrix Methods
Solving Anovas as Regression Problems: General Linear Models
Analysis of Covariance (Ancova)
Curvilinear Regression
Effect Size, Power, and Sample Size in Multiple Regression
Advanced Topics in Regression and Correlation
Analysis of Frequencies
Introduction to Tests for Goodness of Fit
Single-Classification Tests for Goodness of Fit
Replicated Tests of Goodness of Fit
Tests of Independence: Two-Way Tables
Analysis of Three-Way Tables
Analysis of Proportions
Randomized Blocks for Frequency Data
Effect Sizes, Power, and Sample Sizes
Meta-Analysis and Miscellaneous Methods
Synthesis of Prior Research Results: Meta-Analysis
Tests for Randomness of Nominal Data: Runs Tests
Isotonic Regression
Application of Randomization Tests to Unconventional Statistics
The Mantel Test of Association Between Two Distance Matrices
The Future of Biometry: Data Analysis
Mathematical Proofs
Introduction to Matrices
Author Index
Subject Index
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