Everyday we face decisions that carry an element of risk and uncertainty. The ability to analyse, communicate and control the level of risk entailed by these decisions remains one of the most pressing challenges to the analyst, scientist and manager. This book presents the foundational issues in risk analysis - expressing risk, understanding what risk means, building risk models, addressing uncertainty, and applying probability models to real problems. The principal aim of the book is to give the reader the knowledge and basic thinking they require to approach risk and uncertainty to support decision making. * Presents a statistical framework for dealing with risk and uncertainty. * Includes detailed coverage of building and applying risk models and methods. * Offers new perspectives on risk, risk assessment and the use of parametric probability models. * Highlights a number of applications from business and industry. * Adopts a conceptual approach based on elementary probability calculus and statistical theory. Foundations of Risk Analysis provides a framework for understanding, conducting and using risk analysis suitable for advanced undergraduates, graduates, analysts and researchers from statistics, engineering, finance, medicine and the physical sciences, as well as for managers facing decision making problems involving risk and uncertainty.
Author(s): Terje Aven
Edition: 1
Publisher: Wiley
Year: 2003
Language: English
Pages: 209
Foundations of Risk Analysis......Page 4
Contents......Page 8
Preface......Page 12
1.1 The Importance of Risk and Uncertainty Assessments......Page 20
1.2 The Need to Develop a Proper Risk Analysis Framework......Page 23
Bibliographic Notes......Page 25
2.1.1 Accident Statistics......Page 26
2.1.2 Risk Analysis......Page 30
2.1.3 Reliability Analysis......Page 43
2.2.1 General Definitions of Economic Risk in Business and Project Management......Page 47
2.2.2 A Cost Risk Analysis......Page 49
2.2.3 Finance and Portfolio Theory......Page 50
2.2.4 Treatment of Risk in Project Discounted Cash Flow Analysis......Page 53
2.3.1 The Classical Approach......Page 55
2.3.2 The Bayesian Paradigm......Page 56
2.3.3 Economic Risk and Rational Decision-Making......Page 58
2.3.4 Other Perspectives and Applications......Page 59
2.3.5 Conclusions......Page 61
Bibliographic Notes......Page 62
3.1 Basic Ideas and Principles......Page 66
3.1.1 Background Information......Page 69
3.1.3 Observable Quantities......Page 70
3.2.1 A Simple Cost Risk Example......Page 71
3.2.2 Production Risk......Page 74
3.2.3 Business and Project Management......Page 76
3.2.4 Investing Money in a Stock Market......Page 77
3.2.5 Discounted Cash Flow Analysis......Page 78
3.3 Accident Risk......Page 79
Bibliographic Notes......Page 81
4 How to Assess Uncertainties and Specify Probabilities......Page 82
4.1.1 Criteria for Evaluating Probabilities......Page 83
4.1.2 Heuristics and Biases......Page 85
4.1.3 Evaluation of the Assessors......Page 86
4.2 Modelling......Page 87
4.2.1 Examples of Models......Page 88
4.2.2 Discussion......Page 89
4.3 Assessing Uncertainty of Y......Page 90
4.3.1 Assignments Based on Classical Statistical Methods......Page 91
4.3.2 Analyst Judgements Using All Sources of Information......Page 92
4.3.3 Formal Expert Elicitation......Page 93
4.3.4 Bayesian Analysis......Page 94
4.4.1 Cost Risk......Page 102
4.4.2 Production Risk......Page 104
4.4.3 Reliability Analysis......Page 105
4.5 Discussion and Conclusions......Page 109
Bibliographic Notes......Page 111
5 How to Use Risk Analysis to Support Decision-Making......Page 114
5.1 What Is a Good Decision?......Page 115
5.1.1 Features of a Decision-Making Model......Page 116
5.1.2 Decision-Support Tools......Page 117
5.1.3 Discussion......Page 122
5.2.1 Accident Risk......Page 125
5.2.2 Scrap in Place or Complete Removal of Plant......Page 127
5.2.3 Production System......Page 132
5.2.4 Reliability Target......Page 133
5.2.5 Health Risk......Page 135
5.2.6 Warranties......Page 138
5.2.7 Offshore Development Project......Page 139
5.2.8 Risk Assessment: National Sector......Page 141
5.2.9 Multi-Attribute Utility Example......Page 143
5.3.1 A Scheme Based on Potential Consequences and Uncertainties......Page 146
5.3.2 A Scheme Based on Closeness to Hazard and Level of Authority......Page 150
Bibliographic Notes......Page 161
6 Summary and Conclusions......Page 164
A.1.1 Types of Probabilities......Page 168
A.1.2 Probability Rules......Page 170
A.1.3 Random Quantities (Random Variables)......Page 174
A.1.4 Some Common Discrete Probability Distributions (Models)......Page 178
A.1.5 Some Common Continuous Distributions (Models)......Page 179
A.1.6 Some Remarks on Probability Models and Their Parameters......Page 183
A.1.7 Random Processes......Page 184
A.2.1 Non-Parametric Estimation......Page 185
A.2.2 Estimation of Distribution Parameters......Page 186
A.2.3 Testing Hypotheses......Page 188
A.2.4 Regression......Page 189
A.3 Bayesian Inference......Page 190
A.3.1 Statistical (Bayesian) Decision Analysis......Page 192
Bibliographic Notes......Page 193
Appendix B Terminology......Page 194
Bibliography......Page 198
Index......Page 206
