Probability, Statistics, and Decision for Civil Engineers (gnv64)

Probability, Statistics, and Decision for Civil Engineers
by Jack R Benjamin PhD and C. Allin Cornell PhD
Dover Publications | June 2014 | ISBN-10: 0486780724 | ePUB | 471 pages | 25.7 mb
http://www.amazon.com/Probability-Statistics-Decision-Engineers-Engineering/dp/0486780724

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.

About the Authors
C. Allin Cornell (1938–2007) was Professor Emeritus of Civil and Environmental Engineering at Stanford University. He helped pioneer the field of Probabilistic Seismic Hazard Analysis (PSHA), which quantifies and predicts the risks and hazards of earthquakes.
Jack R. Benjamin (1917–98) was Professor Emeritus of Civil and Environmental Engineering at Stanford University, where he taught for 25 years.

CONTENTS
Preface
Introduction
Chapter 1 - Data Reduction
Chapter 2 - Elements of Probability Theory
Chapter 3 - Common Probabilistic Models
Chapter 4 - Probabilistic Models and Observed Data
Chapter 5 - Elementary Bayesian Decision Theory
Chapter 6 - Decision Analysis of Independent Random Processes
Appendix A Tables
Appendix B Derivation of the Asymptotic Extreme-value Distribution
Name Index
Subject Index