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 An
Introduction to Biostatistics
Thomas Glover and Kevin Mitchell
Now available from Waveland Press, this accessible, complete introduction to the use of statistics in the biological sciences emphasizes the relationships among probability, probability distributions, and hypothesis testing. Designed for sophomore- and junior-level students, there are examples throughout the text taken from many areas in the life sciences, including genetics, physiology, ecology, agriculture, and medicine. The authors highlight the expected value of various test statistics under the null and research hypotheses as a way to understand the methodology of hypothesis testing. In addition, they present nonparametric alternatives to many situations along with the usual parametric analysis.
 $46.95 list, 416 pages 10-digit ISBN: 1-57766-458-2 13-digit ISBN: 978-1-57766-458-1 © 2002 Instructor's Answer Manual available The text is well organized and clear, quite suitable for an introductory-level course in statistics for the biological sciences. The sets of problems are very relevant and help solidify the concepts. Frank Siewerdt, University of Maryland I am very impressed with this text. I especially like the number and diversity of the problems at the end of each chapter. The low cost and accompanying CD is also attractive. Steven Slack, University of Memphis The examples are excellent and the text is very student friendly. Kipp Kruse, Eastern Illinois University Nice job! The book is updated, now includes a CD, and is less than one-half the price. It is the perfect size (amount of material) for a solid undergraduate biostatistics course. Marc Albrecht, University of Nebraska 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: Variance, Standard Deviation, and Range / Descriptive Statistics for Frequency Tables or Grouped Data / The Effect of Coding Data / Tables and Graphs / Quartiles and Box Plots / Accuracy, Precision, and the 30300 Rule / Problems 2. Introduction to Probability Definitions / Use of Permutations and Combinations / Introduction to Set Theory and Venn Diagrams / Axioms and Rules of Probability / The Application of Probability Rules to Mendelian Genetics Problems / Problems 3. Probability Distributions Discrete Random Variables / The Binomial Distribution / The Poisson Distribution / Continuous Random Variables / The Normal Distribution / The Standard Normal Distribution / Problems 4. Sampling Distributions Definitions / Distribution of the Sample Mean / Confidence Intervals for the Population Mean / Confidence Intervals for the Population Variance / Population Proportion Confidence Intervals / Problems 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 / Problems 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 / The Wilcoxon Signed-Rank Test: Alternative Method / Problems 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 / Confidence Intervals for MX MY / The Sign Test and Paired Data / The Wilcoxon Signed-Rank Test for Paired Data / Problems 8. k-Sample Tests of Hypothesis: The Analysis of Variance One-Way Classification, Completely Randomized Design with Fixed Effects: Model I ANOVA / Mean Separation Techniques for Model I ANOVAs / Model II ANOVA / The Kruskal-Wallis Test: A Nonparametric Analog to a Model I One-Way ANOVA / Problems 9. Two-Factor Analysis Randomized Complete Block Design ANOVA / Factorial Design Two-Way ANOVA / The Friedman k-Sample Test: Matched Data / Problems 10. Linear Regression and Correlation Simple Linear Regression / Simple Linear Correlation Analysis / Correlation Analysis Based on Ranks / Problems 11. Goodness of Fit Tests for Categorical Data The Binomial Test / The Chi-Square Test for Goodness of Fit / The Chi-Square Test for r x k Contingency Tables / Kolmogorov-Smirnov Test / Problems 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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