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| Probabilistic risk analysis differs from other areas of applied science because it attempts to model events that （almost） never occur. When such an event does occur then the underlying systems and organizations are often changed so that the event cannot occur in the same way again. Because of this, the probabilistic risk analyst must have a strong conceptual and mathematical background. The first chapter surveys the history of risk analysis applications. Chapter 2 explains why probability is used to model uncertainty and why we adopt a subjective definition of probability in spite of its limitations. Chapters 3 and 4 provide the technical background in probability and statistics that is used in the rest of the book. The remaining chapters are more-or-less technically independent of each other, except that Chapter 7 must follow Chapter 6, and 14 should follow 13. The final chapter gives a broad overview of risk measurement problems and looks into the future of risk analysis. |
| Illustrations Tables Preface Part I: Introduction 1 Probabilistic risk analysis 1.1 Historical overview 1.1.1 The aerospace sector 1.1.2 The nuclear sector 1.1.3 The chemical process sector 1.1.4 The less recent past 1.2 What is the definition of risk 1.3 Scope of probabilistic risk analyses 1.4 Risk analysis resources 1.4.1 Important journals 1.4.2 Handbooks 1.4.3 Professional organizations 1.4.4 Internet Part II: Theoretical issues and background 2 What is uncertainty 2.1 The meaning of meaning 2.2 The meaning of uncertainty 2.3 Probability axioms 2.3.1 Interpretations 2.4 Savage''s theory of rational decision 2.4.1 Savage''s axioms 2.4.2 Quantitative probability 2.4.3 Utility 2.4.4 Observation 2.5 Measurement of subjective probabilities 2.6 Different types of uncertainty 2.7 Uncertainty about probabilities 3 Probabilistie methods 3.1 Review of elementary probability theory 3.2 Random variables 3.2.1 Moments 3.2.2 Seve |
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