This edition is a reprint of the second edition published in 2000 by Brooks/Cole and then Cengage Learning.

Principles of Biostatistics is aimed at students in the biological and health sciences who wish to learn modern research methods. It is based on a required course offered at the Harvard School of Public Health. In addition to these graduate students, many health professionals from the Harvard medical area attend as well.

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.

All supplements, including a manual for students with solutions for odd-numbered exercises, a manual for instructors with solutions to all exercises, and selected data sets, are available at https://www.crcpress.com/9781138593145.


chapter 1|6 pages


chapter 2|31 pages

Data Presentation

chapter 3|28 pages

Numerical Summary Measures

chapter 4|31 pages

Rates and Standardization

chapter 5|28 pages

Life Tables

chapter 6|37 pages


chapter 7|34 pages

Theoretical Probability Distributions

chapter 8|18 pages

Sampling Distribution of the Mean

chapter 9|18 pages

Confidence Intervals

chapter 10|27 pages

Hypothesis Testing

chapter 11|26 pages

Comparison of Two Means

chapter 12|17 pages

Analysis of Variance

chapter 13|21 pages

Non Parametric Methods

chapter 14|19 pages

Inference on proportions

chapter 15|32 pages

Contingency Tables

chapter 16|24 pages

Multiple 2 × 2 Contingency Tables

chapter 17|17 pages


chapter 18|34 pages

Simple linear regression

chapter 19|21 pages

Multiple Regression

chapter 20|18 pages

Logistic Regression

chapter 21|26 pages

Survival Analysis

chapter 22|12 pages

Sampling Theory