Multivariate Statistical Methods in Quality Management [NOOK Book]

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...

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Multivariate Statistical Methods in Quality Management

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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

Read More Show Less

Editorial Reviews

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.

Read More Show Less

Product Details

  • ISBN-13: 9780071501378
  • Publisher: McGraw-Hill Education
  • Publication date: 2/25/2004
  • Sold by: Barnes & Noble
  • Format: eBook
  • Edition number: 1
  • Pages: 299
  • File size: 17 MB
  • Note: This product may take a few minutes to download.

Meet the Author

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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Table of Contents

Preface
Ch. 1 Multivariate statistical methods and quality 1
Ch. 2 Graphical multivariate data display and data stratification 25
Ch. 3 Introduction to multivariate random variables, normal distribution, and sampling properties 47
Ch. 4 Multivariate analysis of variance 81
Ch. 5 Principal component analysis and factor analysis 97
Ch. 6 Discriminant analysis 161
Ch. 7 Cluster analysis 181
Ch. 8 Mahalanobis distance and Taguchi method 201
Ch. 9 Path analysis and the structural model 223
Ch. 10 Multivariate statistical process control 243
App. : Probability distribution tables 271
References 291
Index 295
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Sort by: Showing 1 Customer Reviews
  • Posted July 30, 2010

    Statistics

    It is a very good tool for those who want to make Research in Statistics

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