A simple, integrated, treatment of probability and statistics:

Book PhotoENGINEERING

UNCERTAINTY AND RISK ANALYSIS

A Balanced Approach to Probability, Statistics,

Stochastic Modeling, and Stochastic Differential Equations

SERGIO E. SERRANO, Ph.D.

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Engineering Uncertainty and Risk Analysis is the much needed, well-rounded, introduction to probability and statistics every engineer must have, regardless of his/her field.



Engineering Uncertainty and Risk Analysis offers an integrated coverage of the subjects of probability, statistics, Monte Carlo simulation, descriptive and inferential statistics, design of experiments, systems reliability, fitting random data to models, analysis of variance (ANOVA), stochastic processes, and stochastic differential equations. While these subjects are normally covered in different treatises or college courses, the author for the first time presents an introduction to the broad field of engineering uncertainty analysis in one comprehensive, friendly, coverage. Starting from the very fundamental concepts, the reader is taken through a journey that gradually exposes subjects traditionally considered as "complex" or "advanced." The focus is on engineering applications, rather than theoretical or mathematical considerations. Each concept is illustrated with several examples (151 solved examples) of relevance in engineering applications (no cards, colored balls, or dice).

Engineering Uncertainty and Risk Analysis illustrates practical applications with the use of modern computer algebra software, such as Maple (50 short computer programs). However, no prior knowledge of Maple is needed. The author gradually introduces the reader to the use of Maple in stochastic and statistical analysis and modeling, starting from the very basic operations through advanced operations.

Engineering Uncertainty and Risk Analysis presents random differential equations as a natural extension to their deterministic counterpart, rather than a special theoretical subject for statisticians or advanced graduate work. The author strives to emulate the courses of differential equations in most college textbooks. This way the reader may associate random differential equations naturally with the deterministic course s/he had. Many examples illustrate the concepts. In addition, new powerful analytical methods to solve non-linear equations are presented for the first time at this level.

Contents: Engineering uncertainty analysis. The concept of probability. Random variables and probability distributions. Simulations of random systems. Systems with jointly-distributed random variables. Estimation theory in engineering. Fitting probability models to data. Regression analysis. Reliability of engineering systems. Design of engineering experiments. Experiments and tests for two or more populations. Stochastic processes. Stochastic differential equations. Conclusion. Statistical tables. Chapter problems. Answers to proposed problems. Bibliography. Index.

Detailed Contents of the Book.

Independent Reviews and Opinions About "Engineering Uncertainty and Risk Analysis."

About the Author: Dr. Sergio E. Serrano has over 20 years of experience teaching as a professor of engineering at the University of Waterloo (Canada), and the University of Kentucky (U.S.A.). He received his Ph.D. degree from the University of Waterloo. He has over 25 years of international experience in consulting and professional engineering practice. He is the author of over 80 publications in scientific journals and books; an editor of the American Society of Civil Engineers Journal of Hydrologic Engineering. Dr. Serrano's main field of research is in stochastic and statistical methods as applied to water resources, environmental engineering, and continuum mechanics in general. He is a pioneer in the development of new analytical solutions of non-linear stochastic differential equations in complex systems subject to hysteresis, transient variability, random media heterogeneity, and scale dependency.

For more information visit Dr. Sergio E. Serrano's web page.

Soft cover, 472 pages, published in 2001, ISBN: 0-9655643-8-X, $89

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