This book, written by engineers for engineers, tackles the subject in a clear, up-to-date manner using a process-orientated approach. It introduces the subjects of mathematical statistics and probability theory, and then addresses model estimation and testing, regression and multivariate methods, analysis of extreme events, simulation techniques, risk and reliability, and economic decision making.
325 examples and case studies from European and American practice are included and each chapter features realistic problems to be solved.
For the second edition new sections have been added on Monte Carlo Markov chain modeling with details of practical Gibbs sampling, sensitivity analysis and aleatory and epistemic uncertainties, and copulas. Throughout, the text has been revised and modernized.
– Well balanced with theory, examples, references and problems.
– Numerous case studies, examples and problems.
– Covers theories and practical examples not available elsewhere.
– New edition has new sections on Monte Carlo Markov chain modelling, Gibbs samply, sensitivity analysis and aleatory and epistemic uncertainties, and cupolas
– Online solutions manual for text problems available to lecturers
Table of Contents
1. Preliminary data analysis.
2. Basic probability concepts.
3. Random variables and their properties.
4. Probability distributions.
5. Model estimation and testing.
6. Methods of regression and multivariate analysis.
7. Frequency analysis of extreme events.
8. Simulation techniques for design.
9. Risk and reliability analysis.
10. Bayesian decision methods and parameter uncertainty.
Glossary of symbols
Tables of selected distributions
Brief answers to selected problems