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Practical Methods for Reliability Data Analysis
Contributor(s): Ansell, J. I. (Author), Phillips, M. J. (Author)

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ISBN: 019853664X     ISBN-13: 9780198536642
Publisher: OUP Oxford
OUR PRICE: $213.75  

Binding Type: Hardcover
Published: December 1994
Qty:

Annotation: This practical introduction to the analysis of data collected from reliability studies offers clear, detailed explanations of the best and most up-to-date techniques available. Topics include survival analysis with covariates, the assessment of systems performance, reliability growth models,
dependency (which encompasses both engineering and statistical approaches), and practical aspects of analysis. A wealth of interesting case studies appear throughout the text, lending "real-world" examples to the more theoretical discussions. Throughout, the authors stress the need for
investigators to understand the background and nature of their data if they are to select the most appropriate analysis method. They also provide in-depth treatments of the mathematical and statistical bases underlying each technique. Accessible and comprehensive, the book will be welcomed by
students, professionals, and statisticians who are interested in the practical aspects of reliability data analysis.

Click for more in this series: Oxford Statistical Science
Additional Information
BISAC Categories:
- Technology & Engineering | Quality Control
- Mathematics | Probability & Statistics - General
- Mathematics | Mathematical Analysis
Dewey: 620.004
LCCN: 94034309
Series: Oxford Statistical Science
Physical Information: 0.77" H x 6.34" W x 9.32" L (1.20 lbs) 256 pages
Features: Bibliography, Illustrated, Index, Table of Contents
 
Descriptions, Reviews, Etc.
Publisher Description:
This practical introduction to the analysis of data collected from reliability studies offers clear, detailed explanations of the best and most up-to-date techniques available. Topics include survival analysis with covariates, the assessment of systems performance, reliability growth models,
dependency (which encompasses both engineering and statistical approaches), and practical aspects of analysis. A wealth of interesting case studies appear throughout the text, lending real-world examples to the more theoretical discussions. Throughout, the authors stress the need for
investigators to understand the background and nature of their data if they are to select the most appropriate analysis method. They also provide in-depth treatments of the mathematical and statistical bases underlying each technique. Accessible and comprehensive, the book will be welcomed by
students, professionals, and statisticians who are interested in the practical aspects of reliability data analysis.
 
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