Six Sigma and Beyond: Statistical Process Control

gives the details of normal distribution, and Chapter 8 covers the central limit theorem. Chapters 9 and 10 discuss basic statistical hypothesis testing procedures. Chapter 11 exposes the readers to the field of design of experiments. Chapter 12 introduces analysis of variance, Chapter 13 covers contingency tables and goodness of fit, and Chapter 14 gives a simple introduction to regression analysis. Chapter 15 concludes the book with a discussion on the available textbooks that can be used as references. An important feature of the book is its use of Microsoft Excel to do many statistical computations. Excel is widely used as a spreadsheet by engineers; therefore, the author feels that many readers of the book will already be familiar with Excel and so will need very little further time to learn to apply Excel to probability and statistics. The book is also accompanied by a CD–ROM containing all of the datasets used in the book and a fully searchable e-book version of the text in Adobe pdf format. Overall, this is a good textbook. But I did not find anything special about it that will make it standout from the multitude of good textbooks on probability and statistics.