Statistical Models in Engineering [Paperback]

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.Probability and Random Variables.

Continuous Statistical Distributions.

Discrete Statistical Distributions.

The Transformation of Variables.

Approximation by Empirical Distributions.

Drawing Conclusions About System Performance from ComponentData.

Probability Plotting and Testing of DistributionalAssumptions.

Tables.

Categorized Bibliography.

Index.

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 Statistl¬