Statistical Models in Engineering

A detailed treatment on the use of statistical models representing physical phenomena. Considers the relevance of the popular normal distribution models and the applicability of exponential distribution in reliability problems. Introduces and discusses the use of alternate models such as gamma, beta and Weibull distributions. Features expansive coverage of system performance and describes an exact method known as the transformation of variables. Deals with techniques on assessing the adequacy of a chosen model including both graphical and analytical procedures. Contains scores of illustrative examples, most of which have been adapted from actual problems.

Gerald J. Hahn, PhD, worked at the GE Global Research Center for 46 years, where he managed its statistics group for 28 years and was elected a Coolidge Fellow, the organization's highest honor, in 1984. A Fellow of the American Statistical Association and American Society for Quality, Dr. Hahn is the author of numerous papers and the coauthor of Statistical Models in Engineering; Statistical Intervals: A Guide for Practitioners; and The Role of Statistics in Business and Industry, all published by Wiley. He has received many professional awards and served as adjunct professor at various universities.

William Q. Meeker, PhD, is a Professor of Statistics and Distinguished Professor of Liberal Arts and Sciences at Iowa State University. He is a Fellow of the American Statistical Association and the American Society for Quality and a past Editor of Technometrics. He is co-author of the books Statistical Methods for Reliability Data with Luis Escobar, and Statistical Intervals: A Guide for Practitioners with Gerald Hahn.