Statistics, Quality Control - General & Miscellaneous

Multivariate Statistical Methods in Quality Management

Name: Multivariate Statistical Methods in Quality Management
Author: Kai Yang
ISBN: 9780071501378

by Kai Yang, Jayant Trewn

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Overview

Multivariate statistical methods are an essential component of quality engineering data analysis. This monograph provides a solid background in multivariate statistical fundamentals and details key multivariate statistical methods, including simple multivariate data graphical display and multivariate data stratification.

* Graphical multivariate data display
* Multivariate regression and path analysis
* Multivariate process control charts
* Six sigma and multivariate statistical methods

About the Author, Kai Yang

Kai Yang, Ph.D., has consulted extensively in many areas of quality and reliability engineering. He is Associate Professor of Industrial and Manufacturing Engineering at Wayne State University, Detroit, Michigan. He lives in West Bloomfield, Michigan.

Jayant Trewn, Ph.D., is a research faculty member at Beaumont Hospital in Royal Oak, Michigan. He is responsible for implementing cutting edge industrial engineering tools in hospital and health care management. Dr. Trewn was a Director of Quality and Productivity Improvement at Vetri Systems, a Lason Company. He was responsible for business process design and improvement in the global business environment.

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Editorials

From The Critics

Yang (industrial and manufacturing engineering, Wayne State University) and Trewn (research faculty, Beaumont Hospital) explain analytical tools for trouble-shooting, root cause analysis, process control, quality improvement, and other applications in business and industry. Writing for quality professionals, they discuss the theory and background of each method and give examples illustrating how these multivariate statistical methods can be used to solve real world problems, then show how to integrate multivariate statistical methods in quality assurance practice and Six Sigma projects. Readers should have some background in univariate statistical concepts and simple data analysis techniques, as well as in matrix algebra.

Sci-Tech Book News

Yang (industrial and manufacturing engineering, Wayne State University)and Trewn (research faculty, Beaumont Hospital) explain analytical tools for trouble-shooting, root cause analysis, process control, quality improvement, and other applications in business and industry. Writing for quality professionals, they discuss the theory and background of each method and give examples illustrating how these multivariate statistical methods can be used to solve real world problems, then show how to integrate multivariate statistical methods in quality assurance practice

and Six Sigma projects. Readers should have some background in univariate statistical concepts and simple data analysis techniques, as well as in matrix algebra.