Statistical methods have become an increasingly important and integral part of an engineering student’s education. This self-contained volume motivates an appreciation of statistical techniques within the context of engineering; many datasets that are used in the chapters and exercises are from engineering sources. Developed by the author over the course of several years, and with classroom use, some specific ideas are formulated on what should be the content in an engineering statistics course.
This book is different from the classical textbooks on engineering statistics in that it emphasizes statistical thinking and methodology for practicing engineers, together with a solid dose of contemporary statistical methodology. The book has many novel features, including the connection that is frequently made between hypothesis tests and confidence intervals. An unusual feature of the book is that computing equations are kept to a minimum, although some have been put in chapter appendices; Minitab is heavily relied on for illustrating various statistical analyses.
The book is organized into 17 chapters. The author has made great efforts in the arrangement of the book so that the content is easy to follow. Standard material, such as the collection of data, measures of location and dispersion, probability distributions, point estimation, confidence intervals, and hypothesis tests, is covered in the first six chapters. Chapter 7 discusses tolerance intervals and prediction intervals. Chapters 8 and 9 discuss linear and multiple regression. Chapters 10, 11, and 12 consider mechanistic models; control charts and quality improvement; and the design of experiments. Chapters 13 through 16 analyze measurement system appraisal, reliability analysis, categorical data, and distribution-free procedures. The last chapter summarizes engineering applications of statistical methods.
This attractive text is written in a precise style that interconnects and builds on discussion, examples, and methods from chapter to chapter. Especially pleasant are the care and attention devoted to details. The comprehensive and easy-to-read style of writing suggests that statistics is fun and exploratory. It will be useful to engineering students for knowing the exact tools to use in a particular application. Bridging the gap between statistics education and real-world applications, this book is ideal for either a one- or two-semester course in engineering statistics.