O SELECȚIE URIAȘĂ
Peste 4 milioane de cărți în engleză la prețuri avantajoase.
ISBN | 9781118217986 |
---|---|
Autor | McCool John I. |
Editura | Wiley |
Limba | english |
Tip copertă | Pevná vazba |
Anul publicării | 2012 |
Număr de pagini | 366 |
Understand and utilize the latest developments inWeibull inferential methods
While the Weibull distribution is widely used in science andengineering, most engineers do not have the necessary statisticaltraining to implement the methodology effectively. Using theWeibull Distribution: Reliability, Modeling, andInference fills a gap in the current literature on the topic, introducing a self-contained presentation of the probabilisticbasis for the methodology while providing powerful techniques forextracting information from data.
The author explains the use of the Weibull distribution and itsstatistical and probabilistic basis, providing a wealth of materialthat is not available in the current literature. The book begins byoutlining the fundamental probability and statistical concepts thatserve as a foundation for subsequent topics of coverage, including:
- Optimum burn-in, age and block replacement, warranties
and renewal theory
- Exact inference in Weibull regression
- Goodness of fit testing and distinguishing theWeibull
from the lognormal
- Inference for the Three Parameter Weibull
Throughout the book, a wealth of real-world examples showcasesthe discussed topics and each chapter concludes with a set ofexercises, allowing readers to test their understanding of thepresented material. In addition, a related website features theauthor's own software for implementing the discussed analyses alongwith a set of modules written in Mathcad(R), and additionalgraphical interface software for performing simulations.
With its numerous hands-on examples, exercises, and softwareapplications, Using the Weibull Distribution is an excellentbook for courses on quality control and reliability engineering atthe upper-undergraduate and graduate levels. The book also servesas a valuable reference for engineers, scientists, and businessanalysts who gather and interpret data that follows the Weibulldistribution