Praise for the Second Edition
"As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available."
―Technometrics
This new edition continues to provide the most current, proven statistical methods for quality control and quality improvement
The use of quantitative methods offers numerous benefits in the fields of industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. Statistical Methods for Quality Improvement, Third Edition guides readers through a broad range of tools and techniques that make it possible to quickly identify and resolve both current and potential trouble spots within almost any manufacturing or nonmanufacturing process. The book provides detailed coverage of the application of control charts, while also exploring critical topics such as regression, design of experiments, and Taguchi methods.
In this new edition, the author continues to explain how to combine the many statistical methods explored in the book in order to optimize quality control and improvement. The book has been thoroughly revised and updated to reflect the latest research and practices in statistical methods and quality control, and new features include:
Incorporating the latest software applications, the author has added coverage on how to use Minitab software to obtain probability limits for attribute charts. new exercises have been added throughout the book, allowing readers to put the latest statistical methods into practice. Updated references are also provided, shedding light on the current literature and providing resources for further study of the topic.
Statistical Methods for Quality Improvement, Third Edition is an excellent book for courses on quality control and design of experiments at the upper-undergraduate and graduate levels. the book also serves as a valuable reference for practicing statisticians, engineers, and physical scientists interested in statistical quality improvement.
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THOMAS P. RYAN, PhD, served on the Editorial Review Board of the Journal of Quality Technology from 1990–2006, including three years as the book review editor. He is an elected Fellow of the American Statistical Association, the American Society for Quality, and the Royal Statistical Society. A former consultant to Cytel Software Corporation, Dr. Ryan currently teaches advanced courses at statistics.com on the design of experiments, statistical process control, and engineering statistics. He is the author of Modern Experimental Design, Modern Regression Methods, Second Edition, and Modern Engineering Statistics, all published by Wiley.
Praise for the Second Edition
"As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available."
—Technometrics
This new edition continues to provide the most current, proven statistical methods for quality control and quality improvement
The use of quantitative methods offers numerous benefits in the fields of industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. Statistical Methods for Quality Improvement, Third Edition guides readers through a broad range of tools and techniques that make it possible to quickly identify and resolve both current and potential trouble spots within almost any manufacturing or nonmanufacturing process. The book provides detailed coverage of the application of control charts, while also exploring critical topics such as regression, design of experiments, and Taguchi methods.
In this new edition, the author continues to explain how to combine the many statistical methods explored in the book in order to optimize quality control and improvement. The book has been thoroughly revised and updated to reflect the latest research and practices in statistical methods and quality control, and new features include:
Updated coverage of control charts, with newly added tools
The latest research on the monitoring of linear profiles and other types of profiles
Sections on generalized likelihood ratio charts and the effects of parameter estimation on the properties of cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) procedures
New discussions on design of experiments that include conditional effects and fraction of design space plots
New material on Lean Six Sigma and Six Sigma programs and training
Incorporating the latest software applications, the author has added coverage on how to use Minitab software to obtain probability limits for attribute charts. New exercises have been added throughout the book, allowing readers to put the latest statistical methods into practice. Updated references are also provided, shedding light on the current literature and providing resources for further study of the topic.
Statistical Methods for Quality Improvement, Third Edition is an excellent book for courses on quality control and design of experiments at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for practicing statisticians, engineers, and physical scientists interested in statistical quality improvement.
Praise for the Second Edition
As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available.
--Technometrics
This new edition continues to provide the most current, proven statistical methods for quality control and quality improvement
The use of quantitative methods offers numerous benefits in the fields of industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. Statistical Methods for Quality Improvement, Third Edition guides readers through a broad range of tools and techniques that make it possible to quickly identify and resolve both current and potential trouble spots within almost any manufacturing or nonmanufacturing process. The book provides detailed coverage of the application of control charts, while also exploring critical topics such as regression, design of experiments, and Taguchi methods.
In this new edition, the author continues to explain how to combine the many statistical methods explored in the book in order to optimize quality control and improvement. The book has been thoroughly revised and updated to reflect the latest research and practices in statistical methods and quality control, and new features include:
Updated coverage of control charts, with newly added tools
The latest research on the monitoring of linear profiles and other types of profiles
Sections on generalized likelihood ratio charts and the effects of parameter estimation on the properties of cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) procedures
New discussions on design of experiments that include conditional effects and fraction of design space plots
New material on Lean Six Sigma and Six Sigma programs and training
Incorporating the latest software applications, the author has added coverage on how to use Minitab software to obtain probability limits for attribute charts. New exercises have been added throughout the book, allowing readers to put the latest statistical methods into practice. Updated references are also provided, shedding light on the current literature and providing resources for further study of the topic.
Statistical Methods for Quality Improvement, Third Edition is an excellent book for courses on quality control and design of experiments at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for practicing statisticians, engineers, and physical scientists interested in statistical quality improvement.
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