| 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: Clarendon Press OUR PRICE: $213.75 Product Type: Hardcover Published: December 1994 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. |
| 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" (1.20 lbs) 256 pages |
| 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. |
