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Second Edition Thomas Glover and Kevin Mitchell
Statistical analysis is increasingly being recognized as a fundamental quantitative skill for all biology students to master. This accessible text provides the necessary foundation for them to do just that. Glover and Mitchell emphasize the application of statistics using examples from many areas of the life sciences, but without sacrificing theoretical rigor. Along with standard parametric analyses, many examples of nonparametric analysis are incorporated to better simulate the situations that undergraduates encounter in their own research projects and to accommodate those readers with more modest backgrounds in mathematics. A large number of end-of-chapter problems provide ample opportunities to apply the concepts presented in the text.
$54.95 list, 487 pages 10-digit ISBN: 1-57766-580-5 13-digit ISBN: 978-1-57766-580-9 © 2008 Instructor's Answer Manual available Table of Contents
1. Introduction to Data Analysis Introduction / Populations and Samples / Variables or Data Types / Measures of Central Tendency: Mean, Median, and Mode / Measures of Dispersion and Variability / Descriptive Statistics for Frequency Tables or Grouped Data / The Effect of Coding Data / Tables and Graphs / Quartiles and Box Plots / Accuracy, Precision, and the 30–300 Rule 2. Introduction to Probability Definitions / Use of Permutations and Combinations / Introduction to Set Theory and Venn Diagrams / Axioms and Rules of Probability / Probability Rules and Mendelian Genetics 3. Probability Distributions Discrete Random Variables / The Binomial Distribution / The Poisson Distribution / Continuous Random Variables / The Normal Distribution / The Standard Normal Distribution 4. Sampling Distributions Definitions / Distribution of the Sample Mean / Confidence Intervals for the Population Mean / Confidence Intervals for the Population Variance / Confidence Intervals for a Population Proportion 5. Introduction to Hypothesis Testing An Overview: The Famous Cornflakes Example / Typical Steps in a Statistical Test of Hypothesis / Type I versus Type II Errors in Hypothesis Testing / Binomial Example of Hypothesis Testing 6. One-Sample Tests of Hypothesis Hypotheses Involving the Mean (μ) / Hypotheses Involving the Variance (σ2) / Nonparametric Statistics and Hypothesis Testing / The One-Sample Sign Test / Confidence Intervals Based on the Sign Test / The One-Sample Wilcoxon Signed-Rank Test 7. Tests of Hypothesis Involving Two Samples Comparing Two Variances / Testing the Difference Between Two Means of Independent Samples / Confidence Intervals for μ1 − μ2 / The Difference Between Two Means with Paired Data / The Wilcoxon Rank-Sum (Mann-Whitney U) Test / The Sign Test and Paired Data / The Wilcoxon Signed-Rank Test for Paired Data 8. k-Sample Tests of Hypothesis: The Analysis of Variance Model I ANOVA / Mean Separation Techniques for Model I ANOVAs / Model II ANOVA / The Kruskal-Wallis Test 9. Two-Factor Analysis Randomized Complete Block Design ANOVA / Factorial Design Two-Way ANOVA / The Friedman k-Sample Test: Matched Data 10. Linear Regression and Correlation Simple Linear Regression / Simple Linear Correlation Analysis / Correlation Analysis Based on Ranks 11. Goodness of Fit Tests for Categorical Data The Binomial Test / Comparing Two Population Proportions / The Chi-Square Test for Goodness of Fit / The Chi-Square Test for r x k Contingency Tables / Kolmogorov-Smirnov Test / The Lilliefors Test Appendix A: Proofs of Selected Results Appendix B: Answers to Even-Numbered Problems Appendix C: Tables of Distributions and Critical Values
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An
Introduction to Biostatistics