Statistical Distributions

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From the reviews:

"Concise and useful summaries of the salient facts and formulas relating to [various] distributions." -Journal of the American Statistical Association

"A worthwhile reference." -Journal of Quality Technology

Since the previous edition of this popular guide to the most commonly used statistical distributions was published in 1993, statistical methods have found many new applications in science, medicine, engineering, business/finance, and the social sciences. To keep pace with these developments and to highlight the growing influence of statistical software and data management techniques, this new edition is now thoroughly updated and revised. Through clear, concise, easy-to-follow presentations, the authors discuss the key facts and formulas for 40 major probability distributions, fine-tune all existing material, and continue to offer ready access to vital information gleaned from hard-to-find places across the literature. Highly useful both as an introduction to basic principles and as a quick reference guide, Statistical Distributions, Third Edition:
* Presents the 40 distributions in alphabetical order
* Provides all key formulas for each distribution
* Adds a new chapter on the Empirical Distribution Function
* Expands the Weibull Distribution to cover the 3 and 5 parameter versions
* Incorporates diagrams and tables illustrating the characteristics of each distribution
* Discusses the types of application for which distributions are used
* Features references to relevant software packages

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A concise useful reference book. Some of the random variate generators are not necessarily the best and computationally economic. seems a bit expensive to me...



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About the author (2000)

MERRAN EVANS, PhD, is Director of Planning and Academic Affairs at Monash University, Victoria, Australia. NICHOLAS HASTINGS, PhD, is Director of the Centre for Asset Management at Queensland University of Technology, Brisbane, Australia. BRIAN PEACOCK, PhD, is Manager of Manufacturing Ergonomics Laboratory, General Motors Technical Center, Warren, Michigan

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