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An integrated coverage of probability, statistics, Monte Carlo simulation, inferential statistics, design of experiments, systems reliability, fitting random data to models, analysis of variance, stochastic processes, and stochastic differential equations for engineers and scientists. The author for first time presents an introduction to the broad field of applied engineering uncertainty analysis in one comprehensive, friendly, coverage.
Each concept is illustrated with several examples of relevance in engineering applications (no cards, colored balls, or dice):
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An integrated coverage of probability, statistics, Monte Carlo simulation, inferential statistics, design of experiments, systems reliability, fitting random data to models, analysis of variance, stochastic processes, and stochastic differential equations for engineers and scientists. The author for first time presents an introduction to the broad field of applied engineering uncertainty analysis in one comprehensive, friendly, coverage.
Each concept is illustrated with several examples of relevance in engineering applications (no cards, colored balls, or dice):
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