Statistical Methods for Reliability Data

<i>Amstat News</i> asked three review editors to rate their top five favorite books in the September 2003 issue. <i>Statistical Methods for Reliability Data</i> was among those chosen. <p>Bringing statistical methods for reliability testing in line with the computer age This volume presents state-of-the-art, computer-based statistical methods for reliability data analysis and test planning for industrial products. <i>Statistical Methods for Reliability Data</i> updates and improves established techniques as it demonstrates how to apply the new graphical, numerical, or simulation-based methods to a broad range of models encountered in reliability data analysis. It includes methods for planning reliability studies and analyzing degradation data, simulation methods used to complement large-sample asymptotic theory, general likelihood-based methods of handling arbitrarily censored data and truncated data, and more. In this book, engineers and statisticians in industry and academia will find:<br /> </p> <ul type=”DISC”> <li>A wealth of information and procedures developed to give products a competitive edge</li> <li>Simple examples of data analysis computed with the S-PLUS system-for which a suite of functions and commands is available over the Internet</li> <li>End-of-chapter, real-data exercise sets</li> <li>Hundreds of computer graphics illustrating data, results of analyses, and technical concepts</li> </ul> <p>An essential resource for practitioners involved in product reliability and design decisions, <i>Statistical Methods for Reliability Data</i> is also an excellent textbook for on-the-job training courses, and for university courses on applied reliability data analysis at the graduate level.<br /> <br /> An Instructor’s Manual presenting detailed solutions to all the problems in the book is available upon requestfrom the Wiley editorial department.</p>