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The Biostatistics course is often found in the schools of public Health, medical schools, and, occasionally, in statistics and biology departments. The population of students in these courses is a diverse one, with varying preparedness. The book assumes the reader has at least two years of high school algebra, but no previous exposure to statistics is required.Written for individuals who might be fearful of mathematics, this book minimizes the technical difficulties and emphasizes the importance of statistics in scientific investigation. An understanding of underlying design and analysis is stressed. The limitations of the research, design and analytical techniques are discussed, allowing the reader to accurately interpret results. Real data, both processed and raw, are used extensively in examples and exercises. Statistical computing packages - MINITAB, SAS and Stata - are integrated. The use of the computer and software allows a sharper focus on the concepts, letting the computer do the necessary number-crunching.

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• Introduction
• Data and Numbers
• Sampling
• Descriptive Tools
• Probability and Life Tables
• Probability Distributions
• Interval Estimation
• Designed Experiments
• Test of Hypothesis
• Nonparametric Tests
• Analysis of Categorical Data
• Analysis of Survival Data
• Test of Hypotheses Based on the Normal Distribution
• Analysis of Variance
• Linear and Logistic Regression
• Appendices
• Index

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CHOICE Review

Although the preface states that this book is designed for graduate or undergraduate students, the level of presentation appears to be somewhat less advanced than Bernard Rosner's Fundamentals of Biostatistics (2nd ed., 1986). The authors assume no prior knowledge of statistical methods. Even though they provide the occasional formula, only rarely is there much effort to motivate the derivation or origin. The motivations are via examples: real data examples are used throughout that stress the context and the relevance to people's lives and well-being and emphasize the importance of proper research design. Each chapter ends with a set of exercises, many based on real data. The book is clearly designed for students in the health sciences, though statistics students would be well advised to examine the examples to see how statistics is applied in the real world. The calculations for the examples in the text are illustrated using MINITAB. Comparable commands to accomplish the same examples using STATA and SAS are shown in the appendix. A well-done book. F. Giesbrecht; North Carolina State University