Multivariate Statistical Methods in Quality Management

Front Cover
McGraw Hill Professional, Mar 17, 2004 - Technology & Engineering - 299 pages

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

 

Selected pages

Contents

Chapter 1 Multivariate Statistical Methods and Quality
1
Chapter 2 Graphical Multivariate Data Display and Data Stratification
25
Chapter 3 Introduction to Multivariate Random Variables Normal Distribution and Sampling Properties
47
Chapter 4 Multivariate Analysis of Variance
81
Chapter 5 Principal Component Analysis and Factor Analysis
97
Chapter 6 Discriminant Analysis
161
Chapter 7 Cluster Analysis
181
Chapter 8 Mahalanobis Distance and Taguchi Method
201
Chapter 9 Path Analysis and the Structural Model
223
Chapter 10 Multivariate Statistical Process Control
243
Probability Distribution Tables
271
References
291
Index
295
Copyright

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Multivariate Statistical Methods in Quality Management
Kai Yang,Jayant Trewn
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Multivariate Statistical Methods in Quality Management
Kai Yang,Jayant Trewn
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Multivariate Statistical Methods in Quality Management
Kai Yang,Jayant Trewn
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Common terms and phrases

analysis of variance analyze centroid characteristics cluster analysis coefficients computed confidence intervals confidence region control chart control limits correlation matrix data mining data visualization dependent variables dimensional variation discriminant analysis discussed distance between cluster eigenvalues equations example factor analysis Figure graphical hypothesis testing linear regression linkage method luminous power MANOVA mean vector measurement data MINITAB multi-vari chart multivariate data set multivariate normal distribution multivariate process control multivariate random variables multivariate statistical methods n₁ objects observations orthogonal array parameters path analysis path diagram plot population mean principal component analysis principal component score product/service pulse reference sample rotation sample covariance matrix scaled Mahalanobis distance shown in Fig Six Sigma Soybean squares stage standard deviation statistical process control structural model subgroup Table Taguchi temperature template underbody univariate statistical variation mode chart waist weight welding trainee X₁

About the author (2004)

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.

Bibliographic information

TitleMultivariate Statistical Methods in Quality Management
AuthorsKai Yang, Jayant Trewn
PublisherMcGraw Hill Professional, 2004
ISBN0071501371, 9780071501378
Length299 pages
Subjects › 

Technology & Engineering / Engineering (General)
  
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