"Common Errors in Statistics (and How to Avoid Them)." Journal of Quality Technology, 37(1), pp. 87–88

The book is clearly written, to the point, and easy to read. It is well suited for self-study by practitioners with an introductory-level background in statistics. The flow of the presentation is logical. In Chapter 1, the author uses several real datasets with different types of recurrence data to motivate the methods and analyses in subsequent chapters. The book contains many real data sets, most of them from the author's own applications dealing with industrial products. There are also quite a few other interesting examples from other fields, including customer purchase behavior at amazon.com, childbirths to statisticians, and bladder cancer tumor recurrences. All

"Teaching Statistics, Resources for Undergraduate Instructors." Journal of Quality Technology, 35(3), p. 332

"Statistical Process Control, The Deming Paradigm and beyond." Journal of Quality Technology, 35(2), pp. 233–234

"The Desk Reference of Statistical Quality Methods." Journal of Quality Technology, 35(1), p. 117

"A Brief Introduction to Probability and Statistics." Journal of Quality Technology, 35(4), p. 427

The latter part of the book (Chapters 13-18) provides discussion of covariance models for more advanced topics. Chapter 13 describes the covariance model and estimation techniques with examples using the SAS procedure MIXED. Chapter 14 describes testing unequal variances using techniques such as Levene's Test, Hartley's F-Max Test, Bartlett's Test and likelihood ratio tests. In this chapter, the authors discuss how to develop and estimate unequal slope models, and how to compare models with parallel and nonparallel lines. Chapter 15 presents analysis of split-plot designs including models for the covariate(s) measured on the whole plot, or the subplot, or both. By way of example, the authors explain how covariance models for split plots and strip plots can be reduced to mixed models and analyzed using PROC MIXED. Chapter 17 extends the results contained in Analysis of Messy Data, Volume II: Nonreplicated Experiments (Milliken and Johnson (1989) and presents a method for increasing the quality of the model using null and non-null partitions. In chapter 18, the authors address topics such as using the covariate to form blocks, covariates in crossover designs, non parametric analysis of covariance, nonlinear modeling of covariates, and mixed modeling for detection of outliers.

"Statistical Case Studies for Industrial Improvement." Journal of Quality Technology, 32(3), p. 296

This book covers all the basic areas in probability and statistics that are covered in most elementary books on mathematical statistics. It is written so that it can be used at the level in which many courses in a mathematical statistics sequence are taught. If one desires to add an introduction at this level to a more advanced study of probability and statistics, this book will provide the supporting material for such a course.

"Introduction to Design and Analysis of Experiments." Journal of Quality Technology, 31(3), pp. 357–358