Design of Experiments: An Introduction Based on Linear Models

This text enables a better appreciation of the fundamental issues involved in designing experiments. Each chapter describes an experiment, with some drawn from the applied science and engineering literature. The author uses designs as the basis to discuss topics, such as blocking, units, and randomization. He covers data analysis through the specific form of the reduced normal equation for each design, basic hypothesis tests, and confidence intervals. The text also explores graphical procedures for presenting data and checking the usual linear model assumptions. It includes statistical computing material as well as R examples in the appendix.