
Applied Probability for Engineers
Ephraim Suhir(Author)
McGraw-Hill Professional (Publisher)
Published on 16. June 1997
Book
Hardback
592 pages
978-0-07-061860-2 (ISBN)
Description
This watershed resource shows how to use various probabilistic methods and approaches in practical problems of engineering and applied science. These methods enable readers to understand the behavior and performance of engineering products in the conditions of variability and uncertainty, and to ensure the effectiveness and durability of these products. Intended for engineers and applied scientists of different specialities, backgrounds, qualifications, and levels of experience, this straightforward and easy-to-use guide offers practical insight into the role of the ``laws of chance'' and causes and effects of variability in numerous design problems encountered in mechanical, structural, materials, reliability, telecommunications, and other areas of engineering. The book contains dozens of practical examples that demonstrate the key role that probabilistic methods can play in the analysis and design of viable and reliable engineering components, products, and systems.
More details
Language
English
Place of publication
United States
Publishing group
McGraw-Hill Education - Europe
Target group
Professional and scholarly
Illustrations
100 illustrations
Dimensions
Height: 234 mm
Width: 160 mm
Thickness: 41 mm
Weight
975 gr
ISBN-13
978-0-07-061860-2 (9780070618602)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Content
Random Events.Discrete Random Variables.Continuous Random Variables.Systems of Random Variables.Functions of Random Variables.Entropy and Information.Random Processes: Correlation Theory.Random Processes: Spectral Theory.Extreme Value Distributions.Reliability.Markovian Processes.Random Fatigue.Random Vibrations.Geometric Tolerance.Random Loads and Responses in Some Engineering Systems.Processing of Random Data.