Book contents
- Frontmatter
- Contents
- List of illustrations
- Preface
- Acknowledgements
- 1 Uncertainty and decision-making
- 2 The concept of probability
- 3 Probability distributions, expectation and prevision
- 4 The concept of utility
- 5 Games and optimization
- 6 Entropy
- 7 Characteristic functions, transformed and limiting distributions
- 8 Exchangeability and inference
- 9 Extremes
- 10 Risk, safety and reliability
- 11 Data and simulation
- 12 Conclusion
- Appendix 1 Common probability distributions
- Appendix 2 Mathematical aspects
- Appendix 3 Answers and comments on exercises
- References
- Index
Preface
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- List of illustrations
- Preface
- Acknowledgements
- 1 Uncertainty and decision-making
- 2 The concept of probability
- 3 Probability distributions, expectation and prevision
- 4 The concept of utility
- 5 Games and optimization
- 6 Entropy
- 7 Characteristic functions, transformed and limiting distributions
- 8 Exchangeability and inference
- 9 Extremes
- 10 Risk, safety and reliability
- 11 Data and simulation
- 12 Conclusion
- Appendix 1 Common probability distributions
- Appendix 2 Mathematical aspects
- Appendix 3 Answers and comments on exercises
- References
- Index
Summary
Probabilistic reasoning is a vital part of engineering design and analysis. Inevitably it is related to decision-making – that important task of the engineer. There is a body of knowledge profound and beautiful in structure that relates probability to decision-making. This connection is emphasized throughout the book as it is the main reason for engineers to study probability. The decisions to be considered are varied in nature and are not amenable to standard formulae and recipes. We must take responsibility for our decisions and not take refuge in formulae. Engineers should eschew standard methods such as hypothesis testing and think more deeply on the nature of the problem at hand. The book is aimed at conveying this line of thinking. The search for a probabilistic ‘security blanket’ appears as futile. The only real standard is the subjective definition of probability as a ‘fair bet’ tied to the person doing the analysis and to the woman or man in the street. This is our ‘rule for life’, our beacon. The relative weights in the fair bet are our odds on and against the event under consideration.
It is natural to change one's mind in the face of new information. In probabilistic inference this is done using Bayes' theorem. The use of Bayesian methods is presented in a rigorous manner. There are approximations to this line of thinking including the ‘classical’ methods of inference. It has been considered important to view these and others through a Bayesian lens.
- Type
- Chapter
- Information
- Decisions under UncertaintyProbabilistic Analysis for Engineering Decisions, pp. xiii - xvPublisher: Cambridge University PressPrint publication year: 2005