John I. McCool 
Using the Weibull Distribution 
Reliability, Modeling, and Inference

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

Table of Content

Chapter 1. Probability

Chapter 2. Discrete and Continuous Random Variables

Chapter 3. Properties of the Weibull Distribution

Chapter 4. Weibull Probability Models

Chapter 5. Estimation in Single Samples

Chapter 6. Sample Size Selection, Hypothesis Testing and Goodness-of-Fit

Chapter 7. The Program Pivotal

Chapter 8. Inference from Multiple Samples

Chapter 9. Weibull Regression

Chapter 10. The Parameter Weibull Distribution

Chapter 11. Factorial Experiments with Weibull Response

About the author

JOHN I. Mc COOL, Ph D, is Professor of Systems Engineering
at Penn State Great Valley School of Graduate Professional Studies.
A Fellow of the American Society for Quality, Dr. Mc Cool previously
served as principal engineering scientist at SKF Industries Inc.,
where he conducted corporate as well as federally sponsored
research projects with the Wright-Patterson Air Force Base, the
Office of Naval Research, the Naval Air Propulsion Center, the
Department of Energy, and the Air Force Office of Scientific
Research.