Engineering Uncertainty and Risk Analysis: A Balanced Approach to Probability, Statistics, Stochastic Modeling, and Stochastic Differential Equations

This text for undergraduate engineering students presents an integrated treatment of the subjects of probability, statistics, stochastic models, and stochastic differential equations which make up the broader field of uncertainty analysis. The focus is more practical than theoretical. Coverage includes, for example, random variables, numerical and analytical modeling, descriptive and inferential statistics, and fitting probabilistic models to experimental data. All of the computational applications use the Maple algebra software. Serrano teaches engineering at the U. of Kentucky. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Dr. Sergio E. Serrano has over 15 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 60 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.