Synopsis
Today's rapidly changing marketplace can seem like a jungle for many professionals. Engineering & Management Press offers the books needed to navigate through the wilderness of business techniques and acronyms. EMP's titles provide practical information and proven business methods for most corporate and industrial environments. Our titles cover crucial, timely topics of importance to businesses and managers today -- management, productivity improvement, quality, and related issues.Quality -- the word is everywhere in the workplace. Companies have learned that quality products and services sell better, last longer, and bring greater customer satisfaction.Design of experiments and analysis of variance may be used to detect problems and defects in manufacturing and other production processes. Statistical methods may also be used to build quality directly into products and services. This book shows how several key statistical equations and graphs, such as probability plots and histograms, can identify and control problems without disrupting operations. This lowers costs and brings an organization ever closer to its quality ideal.
Review
The author of any publication which attempts to make the application of the principle of statistical analysis accessible to professionals not interested in theory but in applicability walks a fine tightrope indeed. Too little theory turns it into a comic book, too much leaves in unused, or worse, unbought. Meet Robert F. Brewer, the Flying Wallenda of statistics, His staged goal in Design Experiments for Process Improvement and Quality Assurance is to provide a "guide for technicians, supervisors, engineers, and managers involved in the planning, implementation and interpretation of industrial experiment, especially those who must work with qualified professional and statisticians," a goal he achieves admirably. Brewer assumes the reader is not versed in mathematical statistics, but does expect the reader to become familiar with standard statistical terms, a not unreasonable expectation. Brewer eschews a mathematical approach in favor of a visually oriented graphical technique, and does so with great clarity and force of argument. This reviewer found Brewer's discussion of chi-square distribution particularly enlightening and user friendly in teaching its application in a college level biology course to test the statistical significance of genetic experiments involving the organisms Drosophila and Sordaria. While not to be confused with an introductory text in statistical methodology, this book is a wonderful reference tool for the non-statistician required to move in circles that demand a working knowledge of statistical principles. -- From Independent Publisher
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