Principles of Biostatistics, Third Edition is a concepts-based introduction to statistical procedures that prepares public health, medical, and life sciences students to conduct and evaluate research. With an engaging writing style and helpful graphics, the emphasis is on concepts over formulas or rote memorization. Throughout the book, the authors use practical, interesting examples with real data to bring the material to life. Thoroughly revised and updated, this third edition includes a new chapter introducing the basic principles of Study Design, as well as new sections on sample size calculations for two-sample tests on means and proportions, the Kruskal-Wallis test, and the Cox proportional hazards model.
- Includes a new chapter on the basic principles of study design.
- Additional review exercises have been added to each chapter.
- Datasets and Stata and R code are available on the book’s website.
The book is divided into three parts. The first five chapters deal with collections of numbers and ways in which to summarize, explore, and explain them. The next two chapters focus on probability and introduce the tools needed for the subsequent investigation of uncertainty. It is only in the eighth chapter and thereafter that the authors distinguish between populations and samples and begin to investigate the inherent variability introduced by sampling, thus progressing to inference. Postponing the slightly more difficult concepts until a solid foundation has been established makes it easier for the reader to comprehend them.
Table of Contents
Part I Variability
2. Descriptive Statistics
3. Rates and Standardization
4. Life Tables
Part II Probability
6. Screening and Diagnostic Tests
7. Theoretical Probability Distributions
8. Sampling Distribution of the Mean
Part III Inference
9. Confidence Intervals
10. Hypothesis Testing
11. Comparison of Two Means
12. Analysis of Variance
13. Nonparametric Methods
14. Inference on Proportions
15. Contingency Tables
17. Simple Linear Regression
18. Multiple Linear Regression
19. Logistic Regression
20. Survival Analysis
21. Sampling Theory
22. Study Design
Marcello Pagano is Professor of Statistical Computing in the Department of Biostatistics at the Harvard School of Public Health. His research in biostatistics is on computer intensive inference and surveillance methods that involve screening methodologies, with their associated laboratory tests, and in obtaining more accurate testing results that use existing technologies.
Kimberlee Gauvreau is Associate Professor in the Department of Biostatistics and Associate Professor of Pediatrics at Harvard Medical School. Dr. Gauvreau’s research focuses on biostatistical issues arising in the field of pediatric cardiology. She also works on the development and validation of methods of adjustment for case mix complexity.
Heather Mattie is Lecturer on Biostatistics and the Co-Director Health Data Science Program at the Harvard School of Public Health.
"Overall, this remains the best resource out there for teaching introductory biostatistics to graduate students in public health and medicine."
-Amy Herring, Duke University
"All in all, this is an excellent manuscript and I commend the authors for writing a compelling text that not only provides a sound, comprehensive introduction to biostatistical methods, but also motivates and illustrates them using engaging and relevant contemporary examples. I eagerly look forward to the forthcoming publication of the third edition."
-Yue Jiang, Duke University