Design for Six Sigma in Technology and Product Development

The authors state that the intended audience is an interdisciplinary one. The sample problems and exercises are taken from such fields as business, the social sciences, and education. The mathematical detail that is provided is at a level that would be appropriate for non-statisticians. This book would not be appropriate for an engineering course in multivariate analysis or an advanced statistics course; there are practically no examples or exercises that would be considered engineering-oriented. The mathematical detail is much less than what is often required in an advanced course in statistics. There is no complete discussion of the multivariate normal distribution, only references to it in various locations. Topics such as Hotelling's T 2 statistic, which is quite useful for engineering students (especially those studying statistical process control), are only briefly mentioned in Chapter 12. This is not to say that students in these areas would not benefit from the explanations and illustrations given in this book. Quite to the contrary, it is often helpful for students to see applications beyond their area of study, and this book does an outstanding job of providing clear and complete applications and interpretations of the techniques.