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The Desk Reference of Statistical Quality Methods, Second Edition
Crossley, Mark L.

ASQ Quality Press, 2007 - 450 pages

average customer review:based on 2 reviews
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The Desk Reference of Statistical Quality Methods

Great! This book contains all the most important statistical methods that any quality professional might use in maintaining and improving their quality management system. All of the methods are listed in alphabetical order for quick and easy reference. Each method is thoroughly explained and the examples are a great way to familiarize yourself with each method. This book should be on every quality professionals bookshelf! I know I will be referencing it practically everyday.


Great book for the Quality Engineer

If you actually want to learn how to apply SPC and other Quality Methods, this is the book for you. What makes this book great is its ability to bridges the concept to application gap that so many books do not. Mark Crossley breaks each tool down using easy-to-follow steps and illustrations that guide the reader through the use of each tool.


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Arranged in alphabetical order for quick reference, this book provides the quality practitioner with a single resource that illustrates, in a practical manner, how to execute specific statistical methods frequently used in the quality sciences. Each method is presented in a stand-alone fashion and includes computational steps, application comments, and a fully illustrated brief presentation on how to use the tool or technique. A plethora of topics have been arranged in alphabetical order, ranging from acceptance sampling control charts to zone format control charts. This reference is accessible for the average quality practitioner who will need a minimal prior understanding of the techniques discussed to benefit from them. Each topic is presented in a standalone fashion with, in most cases, several examples detailing computational steps and application comments. This second edition includes new sections on advanced SPC applications, reliability applications, and Simplex Optimization. There are expansions in the sections on process capability analysis, hypothesis testing, and design of experiments.


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