Overview
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 TOOLSThere'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
Full Product Details
Author: Kai Yang ,
Jayant Trewn
Publisher: McGraw-Hill Education - Europe
Imprint: McGraw-Hill Professional
Dimensions:
Width: 15.80cm
, Height: 2.80cm
, Length: 23.10cm
Weight: 0.595kg
ISBN: 9780071432085
ISBN 10: 0071432086
Pages: 299
Publication Date: 16 March 2004
Audience:
Professional and scholarly
,
Professional & Vocational
Format: Hardback
Publisher's Status: Active
Availability: Out of stock
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.
Reviews
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 20040601
Author Information
McGraw-Hill authors represent the leading experts in their fields and are dedicated to improving the lives, careers, and interests of readers worldwide McGraw-Hill authors represent the leading experts in their fields and are dedicated to improving the lives, careers, and interests of readers worldwide
