Understand and utilize the latest developments in Weibull inferential methods While the Weibull distribution is widely used in science and engineering, most engineers do not have the necessary statistical training to implement the methodology effectively. Using the Weibull Distribution: Reliability, Modeling, and Inference fills a gap in the current literature on the topic, introducing a self-contained presentation of the probabilistic basis for the methodology while providing powerful techniques for extracting information from data. The author explains the use of the Weibull distribution and its statistical and probabilistic basis, providing a wealth of material that is not available in the current literature. The book begins by outlining the fundamental probability and statistical concepts that serve 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 the Weibull from the lognormal Inference for the Three Parameter Weibull Throughout the book, a wealth of real-world examples showcases the discussed topics and each chapter concludes with a set of exercises, allowing readers to test their understanding of the presented material. In addition, a related website features the author's own software for implementing the discussed analyses along with a set of modules written in Mathcad , and additional graphical interface software for performing simulations. With its numerous hands-on examples, exercises, and software applications, Using the Weibull Distribution is an excellent book for courses on quality control and reliability engineering at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for engineers, scientists, and business analysts who gather and interpret data that follows the Weibull distribution

Understand and utilize the latest developments inWeibull inferential methodsWhile 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 topicintroducing 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 coverageincluding:* Optimum burn-in, age and block replacementwarrantiesand renewal theory* Exact inference in Weibull regression* Goodness of fit testing and distinguishing theWeibullfrom the lognormal* Inference for the Three Parameter WeibullThroughout 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®, 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

Chapter 1. ProbabilityChapter 2. Discrete and Continuous Random VariablesChapter 3. Properties of the Weibull DistributionChapter 4. Weibull Probability ModelsChapter 5. Estimation in Single SamplesChapter 6. Sample Size Selection, Hypothesis Testing and Goodness-of-FitChapter 7. The Program PivotalChapter 8. Inference from Multiple SamplesChapter 9. Weibull RegressionChapter 10. The Parameter Weibull DistributionChapter 11. Factorial Experiments with Weibull Response