- We will send in 10–14 business days.
/images/books/2892656/9780198536642.jpg)
- Author: J I Ansell
- Publisher: Clarendon Press
- ISBN-10: 019853664X
- ISBN-13: 9780198536642
- Format: 16.1 x 23.7 x 2 cm, hardcover
- Language: English
- SAVE -10% with code: EXTRA
Reviews
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.
EXTRA 10 % discount with code: EXTRA
The promotion ends in 17d.00:24:06
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: J I Ansell
- Publisher: Clarendon Press
- ISBN-10: 019853664X
- ISBN-13: 9780198536642
- Format: 16.1 x 23.7 x 2 cm, hardcover
- Language: English English
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.
Reviews