Applied Life Data Analysis
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.
"Many examples drawn from the author’s experience of engineering applications are used to illustrate the theoretical results, which are presented in a cookbook fashion...it provides an excellent practical guide to the analysis of product-life data."
Special Programme of Research in Human Reproduction
World Health Organization
Review in Biometrics, September 1983
Now a classic, Applied Life Data Analysis has been widely used by thousands of engineers and industrial statisticians to obtain information from life data on consumer, industrial, and military products. Organized to serve practitioners, this book starts with basic models and simple informative probability plots of life data. Then it progresses through advanced analytical methods, including maximum likelihood fitting of advanced models to life data. All data analysis methods are illustrated with numerous clients' applications from the author's consulting experience.
About the Author.
1. Overview and Background.
2. Basic Concepts and Distributions for Product Life.
3. Probability Plotting of Complete and Singly Censored Data.
4. Graphical Analysis of Multiply Censored Data.
5. Series Systems and Competing Risks.
6. Analysis of Complete Data.
7. Linear Methods for Singly Censored Data.
8. Maximum Likelihood Analysis of Multiply Censored Data.
9. Analyses of Inspection Data (Qualtal-Response and Interval Data).
10. Comparisons (Hypothesis Tests) For Complete Data.
11. Comparisons with Linear Estimators (Singly Censored and Complete Data).
12. Maximum Likelihood Comparisons (Multiply Censored and Other Data).
13. Survey of Other Topics.
Appendix A. Tables..
American Society for Quality awarded Dr. Wayne Nelson of Schenectady, New York the 2003 Shewhart Medal. The Medal honors his outstanding technical leadership, particularly for innovative developments and applications of theory and methods for analyzing quality, reliability, and accelerated test data, and for widely disseminating such developments through his books and many publications, talks, and courses.
The Shewhart Medal for outstanding technical leadership is named after Dr. Walter A. Shewhart, who pioneered statistical methods for controlling and improving the quality of manufactured products. These methods contributed significantly to the United States' war effort in World War II. Subsequently taken to Japan by Dr. W. Edwards Deming, these methods revolutionized Japan's industries. Today these methods are part of widely used Six Sigma training on how to improve the quality of products and services.
The American Society for Quality is the world's largest professional society dedicated to the improved quality of products and services. It serves its members and the public through a variety of educational activities, including conferences, training courses, journals, and books.
Dr. Nelson is a graduate of the California Institute of Technology (Caltech) and the Univiversity of Illinois. Formerly with GE Research & Development, he now privately consults and gives courses for companies, professional societies, and universities. For his technical contributions, he was elected a Fellow of the American Society for Quality, the American Statistical Association, and the Institute of Electrical and Electronic Engineers. He recently spent four months in Argentina on a Fulbright Award, lecturing on analysis of product reliability data.
"...an excellent addition to a six-sigma program...as well as a useful resource for the reliability engineer or student in statistics. The book is also applicable to many other fields..." (IEEE Electrical Insulation Magazine, July/August 2005)
“…extremely useful for courses on life data analysis, statistical quality control and product marketing.” (Zentralblatt Math, Vol.1054, No.05, 2005)