Statistical Methods for Reliability Data

Beschreibung

Amstat News asked three review editors to rate their topfive favorite books in the September 2003 issue. StatisticalMethods for Reliability Data was among those chosen. Bringing statistical methods for reliability testing in linewith the computer age This volume presents state-of-the-art,computer-based statistical methods for reliability data analysisand test planning for industrial products. Statistical Methodsfor Reliability Data updates and improves establishedtechniques as it demonstrates how to apply the new graphical,numerical, or simulation-based methods to a broad range of modelsencountered in reliability data analysis. It includes methods forplanning reliability studies and analyzing degradation data,simulation methods used to complement large-sample asymptotictheory, general likelihood-based methods of handling arbitrarilycensored data and truncated data, and more. In this book, engineersand statisticians in industry and academia will find: * A wealth of information and procedures developed to giveproducts a competitive edge * Simple examples of data analysis computed with the S-PLUSsystem-for which a suite of functions and commands is availableover the Internet * End-of-chapter, real-data exercise sets * Hundreds of computer graphics illustrating data, results ofanalyses, and technical concepts An essential resource for practitioners involved in productreliability and design decisions, Statistical Methods forReliability Data is also an excellent textbook for on-the-jobtraining courses, and for university courses on applied reliabilitydata analysis at the graduate level. An Instructor's Manual presenting detailed solutions to all theproblems in the book is available upon requestfrom the Wileyeditorial department.

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William Q. Meeker

Themen in »Statistical Methods for Reliability Data«

Qualität, Produktivität u. Zuverlässigkeit Quality, Productivity & Reliability Statistics Statistik Technische Zuverlässigkeit

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"...provides state-of-the-art developments in reliabilitytheory and applications." (Journal of Statistical Computationand Simulation, June 2005)This title has been awarded the: Association of American Publishers Professional/Scholarly Publishing Division Award for Excellence and Innovation in Engineering
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