Book description
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
introduces readers to the concepts and techniques for solving problems
and improving managerial processes using Six Sigma and Lean Six Sigma.
Written by knowledgeable professionals working in the field today, the
book offers thorough coverage of the statistical topics related to
effective Six Sigma and Lean Six Sigma practices, including:
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Discrete random variables and continuous random variables
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Sampling distributions
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Estimation and hypothesis tests
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Chi-square tests
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Analysis of variance
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Linear and multiple regression
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Measurement analysis
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Survey methods and sampling techniques
The authors provide numerous opportunities for readers to test their
understanding of the presented material, as the real data sets, which
are incorporated into the treatment of each topic, can be easily
worked with using Microsoft Office Excel, Minitab, MindPro, or
Oracle's Crystal Ball software packages. Examples of successful,
complete Six Sigma and Lean Six Sigma projects are supplied in many
chapters along with extensive exercises that range in level of
complexity. The book is accompanied by an extensive FTP site that
features manuals for working with the discussed software packages
along with additional exercises and data sets. In addition, numerous
screenshots and figures guide readers through the functional and
visual methods of learning Six Sigma and Lean Six Sigma.
Practitioner's Guide to Statistics and Lean Six Sigma for Process
Improvements is an excellent book for courses on Six Sigma and
statistical quality control at the upper-undergraduate and graduate
levels. It is also a valuable reference for professionals in the
fields of engineering, business, physics, management, and finance.
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.
