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)
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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)
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