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Probability, Statistics, and Decision for Civil Engineers—
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The Story
Designed as a primary text for civil engineering courses, as a supplementary text for courses in other areas, or for self-study by practicing engineers, this text covers the development of decision theory and the applications of probability within the field. Extensive use of examples and illustrations helps readers develop an in-depth appreciation for the theory's applications, which include strength of materials, soil mechanics, construction planning, and water-resource design.
A focus on fundamentals includes such subjects as Bayesian statistical decision theory, subjective probability, and utility theory. This makes the material accessible to engineers trained in classical statistics and also provides a brief elementary introduction to probability. The coverage also addresses in detail the methods for analyzing engineering economic decisions in the face of uncertainty. An Appendix of tables makes this volume particularly useful as a reference text.
A focus on fundamentals includes such subjects as Bayesian statistical decision theory, subjective probability, and utility theory. This makes the material accessible to engineers trained in classical statistics and also provides a brief elementary introduction to probability. The coverage also addresses in detail the methods for analyzing engineering economic decisions in the face of uncertainty. An Appendix of tables makes this volume particularly useful as a reference text.
Reprint of the McGraw-Hill Book Company, New York, 1970 edition.
dover books, dover books on engineering, civil engineering, civil engineering reference, civil engineering science, engineering, engineering reference, engineering science, probability, statistics, decision for civil engineers, self study, reference, statistical decision theory, subjective probability, utility theory, mathematics, college, engaging, experiments, theoretical, phenomenon, students and teachers, school, career;Probability, Statistics, and Decision; Civil Engineering; C. Allin Cornell; Jack R. BenjaminDescription
Designed as a primary text for civil engineering courses, as a supplementary text for courses in other areas, or for self-study by practicing engineers, this text covers the development of decision theory and the applications of probability within the field. Extensive use of examples and illustrations helps readers develop an in-depth appreciation for the theory's applications, which include strength of materials, soil mechanics, construction planning, and water-resource design.
A focus on fundamentals includes such subjects as Bayesian statistical decision theory, subjective probability, and utility theory. This makes the material accessible to engineers trained in classical statistics and also provides a brief elementary introduction to probability. The coverage also addresses in detail the methods for analyzing engineering economic decisions in the face of uncertainty. An Appendix of tables makes this volume particularly useful as a reference text.
A focus on fundamentals includes such subjects as Bayesian statistical decision theory, subjective probability, and utility theory. This makes the material accessible to engineers trained in classical statistics and also provides a brief elementary introduction to probability. The coverage also addresses in detail the methods for analyzing engineering economic decisions in the face of uncertainty. An Appendix of tables makes this volume particularly useful as a reference text.
Reprint of the McGraw-Hill Book Company, New York, 1970 edition.
dover books, dover books on engineering, civil engineering, civil engineering reference, civil engineering science, engineering, engineering reference, engineering science, probability, statistics, decision for civil engineers, self study, reference, statistical decision theory, subjective probability, utility theory, mathematics, college, engaging, experiments, theoretical, phenomenon, students and teachers, school, career;Probability, Statistics, and Decision; Civil Engineering; C. Allin Cornell; Jack R. Benjamin
