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Practical Acceptance Sampling: A Hands-On Guide [2nd Edition] Paperback – July 14 2016
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Practical Acceptance Sampling is a hands-on introduction to the inspection of products and services for quality assurance using statistically-based sampling plans.
In today’s era of global supply chains, the path from raw materials to final product often takes place over multiple companies and across multiple continents. Acceptance sampling is key in the 21st century environment.
Acceptance sampling plans provide criteria and decision rules for determining whether to accept or reject a batch based on a sample. They are therefore widely used by manufacturers, suppliers, contractors and subcontractors, and service providers in a wide range of industries.
The book introduces readers to the most popular sampling plans, including Military Standards and civilian ISO and ANSI/ASQC/BS standards. It covers the design, choice and performance evaluation of different types of plans, including single- and double-stage plans, rectifying and non-rectifying plans, plans for pass/fail and continuous measurements, continuous sampling plans, and more.
Practical Acceptance Sampling is suitable for courses on quality control and for quality practitioners with basic knowledge of statistics. It offers clear explanations, examples, end-of-chapter problems, and illustrations of state-of-the-art online resources. Methods are illustrated using Microsoft Excel, online calculators, and SQCOnline.com. However, any statistical software can be used with the book.
A companion website to the book is available at www.SamplingBook.com
- ISBN-100991576675
- ISBN-13978-0991576678
- Edition2
- Publication dateJuly 14 2016
- LanguageEnglish
- Dimensions17.78 x 0.61 x 25.4 cm
- Print length106 pages
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About the Author
Product details
- Publisher : Axelrod Schnall Publishers; 2 edition (July 14 2016)
- Language : English
- Paperback : 106 pages
- ISBN-10 : 0991576675
- ISBN-13 : 978-0991576678
- Item weight : 200 g
- Dimensions : 17.78 x 0.61 x 25.4 cm
- Best Sellers Rank: #1,313,456 in Books (See Top 100 in Books)
- #458 in Production Quality Control
- #690 in Quality Control
- #1,053 in Quality Control Management (Books)
- Customer Reviews:
About the author

Galit Shmueli is Distinguished Professor at the Institute of Service Science, National Tsing Hua University, Taiwan. She is also a visiting scholar at Academia Sinica's Institute of Statistical Science. Between 2011-2014 she was the SRITNE Chaired Professor of Data Analytics and Associate Professor of Statistics & Information Systems at the Indian School of Business. She is best known for her research and teaching in business analytics, with a focus on statistical and data mining methods for contemporary data and applications in information systems and healthcare.
Dr. Shmueli's research has been published in the statistics, management, information systems, and marketing literature. She authored/co-authored over ninety journal articles, books, textbooks and book chapters, including the popular textbook Data Mining for Business Intelligence and Practical Time Series Forecasting. Dr. Shmueli is an award-winning teacher and speaker on data analytics.
She has taught at Carnegie Mellon University, University of Maryland, the Israel Institute of Technology, Statistics.com and the Indian School of Business. Her experience spans business and engineering students and professionals, both online and on-ground. Dr. Shmueli teaches courses on data mining, statistics, forecasting, data visualization, and industrial statistics.
For more information, visit www.galitshmueli.com
Customer reviews
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pro: The book gives reasonable good overview of the various sampling method out there.
Con: This book deals with statistics, which is non-intuitive material by nature, hard to grasp even for people which deals with statistics on daily basis (I happen to be such a person). Unfortunately, the writer did not invest enough effort to alleviate the non-intuitiveness of the material (by almost completely neglecting graphics, by not giving clear and concise definitions for each parameter, variable and equations used, by not explaining the Excel functions used, etc.). In addition, there are many inaccuracies in the text and equations which makes it even harder to understand.
Another issue are the cross-references (page numbers, equation numbers and figures numbers), in the kindle version, do not work properly (I'm not sure I can blame this on the writer, but she is responsible).
Therefore, I would not recommend this book to most people.
ZvikaBK

