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Multivariate Statistical Methods in Quality Management

Autor Kai Yang, Jayant Trewn
en Limba Engleză Hardback – 16 mar 2004


Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality,  authenticity, or access to any online entitlements included with the product.




UPGRADE MANUFACTURING AND SERVICE PERFORMANCE WITH POWERFUL STATISTICAL TOOLS
There's no better way to master the most rigorous statistical methods available for analyzing the performance of complex systems -- Multivariate Statistical Methods in Quality Management teaches powerful analytic tools for troubleshooting, root cause analysis, process control, quality improvement, and many other applications. Written by statistics experts who specialize in reliability and quality engineering, this unique resource introduces the fundamentals and then demonstrates how to:

*Choose the best method for each data set
* Make complex data intelligible with graphical tools
* Coax important hidden information from data with graphical 3-D software and numerical multivariate data stratification
* Perform data reduction with principal component analysis, factor analysis, and discriminant analysis
* Apply multivariate methods in Six Sigma enterprises
* Get clarification from case studies, models, and 50 illustrations
* Uncover the source of problems and pinpoint solutions in arenas from manufacturing processes to sales performance and beyond

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Specificații

ISBN-13: 9780071432085
ISBN-10: 0071432086
Pagini: 299
Dimensiuni: 158 x 231 x 28 mm
Greutate: 0.6 kg
Ediția:New.
Editura: McGraw Hill Education
Colecția McGraw-Hill
Locul publicării:United States

Cuprins

Chapter 1: Multivariate Statistical Methods and Quality

Chapter 2: Graphical Multivariate Data Display and Data Stratification

Chapter 3: Introduction to Multivariate Random Variables, Normal Distribution, and Sampling Properties

Chapter 4: Multivariate Analysis of Variance

Chapter 5: Principal Component Analysis and Factor Analysis

Chapter 6: Discriminant Analysis

Chapter 7: Cluster Analysis

Chapter 8: Mahalanobis Distance and Taguchi Method

Chapter 9: Path Analysis and the Structural Method

Chapter 10: Multivariate Statistical Process Control

APPENDIX: PROBABILITY DISTRIBUTION TABLES

REFERENCES

INDEX