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Applied data analysis for process improvement : a practical guide to six sigma black belt statistics

Author: James L Lamprecht; Annemieke Hytinen; Paul O'Mara
Publisher: Milwaukee, Wisconsin : ASQ Quality Press, 2005. ©2005
Edition/Format:   eBook : Document : EnglishView all editions and formats
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Lamprecht, James L., 1947-
Applied data analysis for process improvement : a practical guide to six sigma black belt statistics.
Milwaukee, Wisconsin : ASQ Quality Press, ©2005
xx, 283 pages
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: James L Lamprecht; Annemieke Hytinen; Paul O'Mara
ISBN: 0873896483 9780873896481
OCLC Number: 891386739
Description: 1 online resource (303 pages) : illustrations
Responsibility: James L. Lamprecht ; acquisitions editor, Annemieke Hytinen ; project editor, Paul O'Mara.

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With the rise of Six Sigma, the use of statistics to analyze and improve processes has once again regained a prominent place in businesses around the world. an increasing number of employees and managers, bestowed with the titles Green Belt, Black Belt, or even Master Black Belts, are asked to apply statistical techniques to analyze and resolve industrial and non-industrial (also known as transactional) problems. These individuals are continuously faced with the daunting task of sorting out the vast array of sophisticated techniques placed at their disposal by an equally impressive array of statistical computer software packages. This book is intended for the ever-growing number of certified Black Belts as well as uncertified others that would like to understand how data can be analyzed. Many courses, including Six Sigma Black Belt courses, do a good job introducing participants to a vast array of sophisticated statistical techniques in as little as ten days, leaning heavily on statistical software packages. Although it is true that one can simplify statistical principles, learning how to interpret results produced by any statistical software requires the understanding of statistics that this book concisely provides.

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