Practitioner's Guide to Statistics and Lean Six Sigma for Process Improvements
This hands-on book presents a complete understanding of Six Sigma and Lean Six Sigma through data analysis and statistical concepts In today's business world, Six Sigma, or Lean Six Sigma, is a crucial tool utilized by companies to improve customer satisfaction, increase profitability, and enhance productivity. Practitioner's Guide to Statistics and Lean Six Sigma for Process Improvements provides a balanced approach to quantitative and qualitative statistics using Six Sigma and Lean Six Sigma methodologies. Emphasizing applications and the implementation of data analyses as they relate to this strategy for business management, this book intr…
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Produktdetails
Weitere Autoren: Mann, Prem S. / Lacke, Christopher J. / Harry, Mikel J. / Hulbert, Richard L.
- ISBN: 978-1-118-21021-5
- EAN: 9781118210215
- Produktnummer: 13871661
- Verlag: Wiley
- Sprache: Englisch
- Erscheinungsjahr: 2011
- Seitenangabe: 832 S.
- Plattform: EPUB
- Masse: 17'806 KB
Über den Autor
Mikel J. Harry, PhD, is President and Chairman of the Board of the Six Sigma Management Institute. He is considered the principal architect of Six Sigma and one of the world's leading authorities in the field. Dr. Harry also focuses his research on applications of experimental design, inferential statistics, and statistical process control. Prem S. Mann, PhD, is Professor and Chair of the Department of Economics at Eastern Connecticut State University. Dr. Mann has published numerous articles in the areas of labor economics, microeconomics, and statistics. He is the author of Introductory Statistics, Seventh Edition (Wiley). Ofelia C. De Hodgins, MS, is a Six Sigma Global Master Black Belt. She has over twenty-five years of consulting experience in manufacturing and finance and has published more than thirty journal articles in the areas of physics, industrial engineering, statistics, and Statistical Process Control (SPC). Richard L. Hulbert, MBA, is Vice President of Systems and Technology for the Bank of New York Mellon. He has more than thirty-five years of industry experience in the areas of network engineering, installation, implementation, network operations of technology infrastructure, distributed systems, market data, and government telecommunications. Christopher J. Lacke, PhD, is Associate Professor of Mathematics at Rowan University. He has published numerous journal articles in his areas of research interest, which include decision analysis, Bayesian analysis, and operations research.
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