This book has been written for an introductory course in probability and statistics for students of engineering and the physical sciences. Each chapter is keynoted by an introductory statement and has a checklist of key terms (with page numbers) at the end. Important formulas, theorems, and rules are set out from the text in boxes. The steps for hypothesis testing are clearly and consistently delineated in each application. Emphasis is also given to confidence interval procedures.

The text has been tested extensively in courses for university students as well as by in-plant training of engineers. The whole book can be covered in a two-semester or three-quarter course consisting of three lectures a week. The book also makes an excellent basis for a one-semester course where the lecturer can choose topics to emphasize theory or application. One of the authors covers most of the first seven chapters, straight-line regression, and the graphic presentation of factorial designs in one semester.

In this fifth edition we have continued to build on the strengths of the previous editions while at the same time bringing in more actual data sets and examples of the application of statistics in scientific investigations. The major changes include the following:

Several new exercises and examples based on actual data and real applications. These enrich the already large collection based on our consulting experiences with engineers from industry and scientific research laboratories.

The section on graphic presentation of 2 and 2 experiments has been improved and expanded. It now works better as a stand alone section for those who want some coverage but dont have time for the whole chapter.

In keeping with modern usage, we have introduced capital letters X, Y, and Z to denote random variables and lowercase letters for their values.

At the request of some users, additional material has been added on joint distributions. This has enabled us to obtain the important properties of expectation and variance. These are now clearly set out in Chapter 5.

To give students an early preview of statistics, descriptive statistics are covered in Chapter 2. Chapters 3 through 6 provide a briet, though rigorous, introduction to the theory of statistics and, together with some of the material in Chapter 15, they are suitable for an introductory semester (or quarter) course on probability and statistics. Chapters 7, 8, and 9 contain conventional material on the key concepts and elementary methods of statistical inference. Chapters 11, 12, and 13 comprise an introduction to some of the standard, though more advanced, topics of experimental design and regression. Chapter 14 stresses the key underlying statistical ideas for quality improvement, and Chapter 15 treats the associated ideas of reliability and the fitting of life length models.

The mathematical background expected of the reader is a year course in calculus; actually, calculus is required mainly for Chapter 5 dealing with basic distribution theory in the continuous case.

We wish to thank Minitab (State College, Pennsylvania) for permission  to include commands and output from their MINITAB software package, and the SAS Institute (Cary, North Carolina) for permission to include output from their SAS package.

Thanks also to Paul M. Berthouex, Jim Evans, Cherilyn Hatfield, David Steinberg, and Steve Verrill for contributing data sets for new examples and exercises. K. T. Wu and S. Sim provided valuable help in checking the manuscript.

All revisions in this edition were the responsibility of R. A. Johnson.