Free eBook Statistical Methods for Reliability Data download
by Luis A. Escobar,William Q. Meeker
Author: Luis A. Escobar,William Q. Meeker
Publisher: Wiley-Interscience; 1 edition (July 24, 1998)
Category: Engineering & Transportation
Size MP3: 1201 mb
Size FLAC: 1957 mb
Format: mbr azw lit docx
Bringing statistical methods for reliability testing in line with the computer age This volume presents . LUIS A. ESCOBAR, PhD, is a Professor in the Department of Experimental Statistics at Louisiana State University.
Statistical Methods for Reliability Data updates and improves established techniques as it demonstrates how to apply the new graphical, numerical, or simulation-based methods to a broad range of models encountered in reliability data analysis.
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Reliability and survival analysis both deal with time to failure data. He said he did not plan to do it because Meeker and Escobar had just finished a work that would be as good as any revision he might want to produce. Much of the methodology is essentially the same. The term reliability is generally used to apply to hardware or software whereas survival analysis is a term for biological systems such as animals or humans. This book includes the standard nonparametric and parametric methods for estimating reliability functions and parameters. Other topics include failure time regression models including the popular Cox proportional hazards model and accelerated life test models.
William Q. Statistical Methods for Reliability Data was among those chosen.
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Reliability in statistics and psychometrics is the overall consistency of a measure. A measure is said to have a high reliability if it produces similar results under consistent conditions. It is the characteristic of a set of test scores that. It is the characteristic of a set of test scores that relates to the amount of random error from the measurement process that might be embedded in the scores. Scores that are highly reliable are accurate, reproducible, and consistent from one testing occasion to another.
Bringing statistical methods for reliability testing in line with the computer age This volume presents state-of-the-art, computer-based statistical . Additional Product Features. Place of Publication.
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Statistical Methods 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 edgeSimple examples of data analysis computed with the S-PLUSsystem-for which a suite of functions and commands is availableover the InternetEnd-of-chapter, real-data exercise setsHundreds 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.