Statistical Methods for Reliability Data Hardcover – July 24, 1998
Author: Visit Amazon's William Q. Meeker Page | Language: English | ISBN: 0471143286 | Format: PDF, EPUB
Statistical Methods for Reliability Data – July 24, 1998
Download Statistical Methods for Reliability Data Hardcover – July 24, 1998 for everyone book mediafire, rapishare, and mirror link Download latest books on mediafire and other links compilation Statistical Methods for Reliability Data – July 24, 1998
Download Statistical Methods for Reliability Data Hardcover – July 24, 1998 for everyone book mediafire, rapishare, and mirror link Download latest books on mediafire and other links compilation Statistical Methods for Reliability Data – July 24, 1998
- Hardcover: 712 pages
- Publisher: Wiley-Interscience; 1 edition (July 24, 1998)
- Language: English
- ISBN-10: 0471143286
- ISBN-13: 978-0471143284
- Product Dimensions: 9.4 x 6.3 x 1.6 inches
- Shipping Weight: 2.6 pounds (View shipping rates and policies)
- Amazon Best Sellers Rank: #594,079 in Books (See Top 100 in Books)
Partial table of contents:
Reliability Concepts and Reliability Data.
Nonparametric Estimation.
Other Parametric Distributions.
Probability Plotting.
Bootstrap Confidence Intervals.
Planning Life Tests.
Degradation Data, Models, and Data Analysis.
Introduction to the Use of Bayesian Methods for Reliability Data.
Failure-Time Regression Analysis.
Accelerated Test Models.
Accelerated Life Tests.
Case Studies and Further Applications.
Epilogue.
Appendices.
References.
Indexes.
Reliability Concepts and Reliability Data.
Nonparametric Estimation.
Other Parametric Distributions.
Probability Plotting.
Bootstrap Confidence Intervals.
Planning Life Tests.
Degradation Data, Models, and Data Analysis.
Introduction to the Use of Bayesian Methods for Reliability Data.
Failure-Time Regression Analysis.
Accelerated Test Models.
Accelerated Life Tests.
Case Studies and Further Applications.
Epilogue.
Appendices.
References.
Indexes.
Reliability data isn't amenable to treatment with the ubiquitous normal distribution, a fact which should catch the attention of any practicing engineer with only that bullet in his gun. Reliability data has other distinguishing features. The data are usually censored, which means the exact failure times are not known so the observations can only provide bounds on the actual failure times. Inferences and predictions usually require extrapolations, making engineering and physics-based modeling an important adjunct to statistical methods. Whereas many *statistical* problems focus on parameter estimation (e.g.: mean, standard deviation), these are not of primary interest to engineers who need specific measures of product reliability (e.g.: failure probabilities, life distribution quintiles, failure rates).
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