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Applied Statistics for Civil and Environmental Engineers
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Civil and environmental engineers need an understanding ofmathematical statistics and probability theory to deal with thevariability that affects engineers structures, soil pressures,river flows and the like. Students, too, need to get to grips withthese rather difficult concepts.This book, written by engineers for engineers, tackles the subjectin a clear, up-to-date manner using a process-orientated approach.It introduces the subjects of mathematical statistics andprobability theory, and then addresses model estimation andtesting, regression and multivariate methods, analysis of extremeevents...
Civil and environmental engineers need an understanding ofmathematical statistics and probability theory to deal with thevariability that affects engineers structures, soil pressures,river flows and the like. Students, too, need to get to grips withthese rather difficult concepts.
This book, written by engineers for engineers, tackles the subjectin a clear, up-to-date manner using a process-orientated approach.It introduces the subjects of mathematical statistics andprobability theory, and then addresses model estimation andtesting, regression and multivariate methods, analysis of extremeevents, simulation techniques, risk and reliability, and economicdecision making.
325 examples and case studies from European and American practiceare included and each chapter features realistic problems to besolved.
For the second edition new sections have been added on Monte CarloMarkov chain modeling with details of practical Gibbs sampling,sensitivity analysis and aleatory and epistemic uncertainties, andcopulas. Throughout, the text has been revised and modernized.
This book, written by engineers for engineers, tackles the subjectin a clear, up-to-date manner using a process-orientated approach.It introduces the subjects of mathematical statistics andprobability theory, and then addresses model estimation andtesting, regression and multivariate methods, analysis of extremeevents, simulation techniques, risk and reliability, and economicdecision making.
325 examples and case studies from European and American practiceare included and each chapter features realistic problems to besolved.
For the second edition new sections have been added on Monte CarloMarkov chain modeling with details of practical Gibbs sampling,sensitivity analysis and aleatory and epistemic uncertainties, andcopulas. Throughout, the text has been revised and modernized.
