<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> <UL TYPE="DISC"> <LI> A wealth of information and procedures developed to give products a competitive edge <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> End-of-chapter, real-data exercise sets <LI> Hundreds of computer graphics illustrating data, results of analyses, and technical concepts</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.