Statistics in Civil Engineering.

Metcalfe, Andrew:

ISBN 10: 0340676604 / ISBN 13: 9780340676608

Edité par London: Arnold, 1997

A propos de cet article

Series: Arnold Applications of Statistics Series. xiii 420p large paperback illustrated cover with dark green lettering, nice clean copy, no names or stamps, as new Language: English.

N° de réf. du vendeur 242578

Détails bibliographiques

• Titre: Statistics in Civil Engineering.
• Éditeur: London: Arnold
• Date de parution: 1997
• Langue: anglais
• ISBN à 10 chiffres: 0340676604
• ISBN à 13 chiffres: 9780340676608
• Reliure: Paperback
• Édition: Edition originale
• État de l'article: Very Good
• Catalogues du vendeur:
  • engineering

A propos de ce titre

Synopsis

Best practice in engineering involves the use of modern statistical techniques. This volume brings these techniques together, and the emphasis is on modelling. The topics include: random number generation, reliability and quality assurance; univariate and multivariate extreme value distributions; regression methods; Bayesian methods; time series analysis; Markov chains and stochastic dynamic programming; variograms and kriging; spectral analysis and wavelets; and design of experiments. The methods are introduced with practical examples, drawn from research and consultancy experience, and the underlying mathematical concepts are clearly explained in an informal manner. Readers are given enough information to write their own programs, but references to useful commercial software are also provided. A brief summary of a typical first course in statistics is included as an appendix.

Présentation de l'éditeur

Best practice in civil engineering involves the use of modern statistical techniques, many of which are only described in the research literature or rather specialist books on specific themes. This book brings these techniques together in the context of civil engineering. The emphasis is on modelling and topics include: random number generation; reliability and quality assurance; univariate and multivariate extreme value distributions; regression methods; Bayesian methods; time series analysis; Markov chains and stochastic dynamic programming; variograms and kriging; spectral analysis and wavelets; and design of experiments.

The methods are introduced with practical examples, drawn from research and consultancy experience, and the underlying mathematical concepts are clearly explained in an informal manner. Readers will be drawn from a wide range of backgrounds and will include civil engineering students at intermediate and advanced levels as well as applied statisticians and engineers in civil engineering consulting practices.