Year: 2003 Language: english Author: Terje Aven Genre: Guide Format: PDF/EPUB Quality: Unknown Pages count: 198 Description: Foundations of Risk Analysis A Knowledge and Decision-Oriented Perspective This book is about foundational issues in risk and risk analysis; how risk should be expressed; what the meaning of risk is; how to understand and use models; how to understand and address uncertainty; and how parametric probability models like the Poisson model should be understood and used. A unifying and holistic approach to risk and uncertainty is presented, for different applications and disciplines. Industry and business applications are highlighted, but aspects related to other areas are included. Decision situations covered include concept optimization and the need for measures to reduce risk for a production system, the choice between alternative investment projects and the use of a type of medical treatment. Additional info: A.1.6 Some Remarks on Probability Models and Their Parameters 164 A.1.7 Random Processes 165 A.2 Classical Statistical Inference 166

Contents

Preface ix 1 Introduction 1 1.1 The Importance of Risk and Uncertainty Assessments 1 1.2 The Need to Develop a Proper Risk Analysis Framework 4 Bibliographic Notes 6 2 Common Thinking about Risk and Risk Analysis 7 2.1 Accident Risk 7 2.1.1 Accident Statistics 7 2.1.2 Risk Analysis 11 2.1.3 Reliability Analysis 24 2.2 Economic Risk 28 2.2.1 General Definitions of Economic Risk in Business and Project Management 28 2.2.2 A Cost Risk Analysis 30 2.2.3 Finance and Portfolio Theory 31 2.2.4 Treatment of Risk in Project Discounted Cash Flow Analysis 34 2.3 Discussion and Conclusions 36 2.3.1 The Classical Approach 36 2.3.2 The Bayesian Paradigm 37 2.3.3 Economic Risk and Rational Decision-Making 39 2.3.4 Other Perspectives and Applications 40 2.3.5 Conclusions 42 Bibliographic Notes 43 3 How to Think about Risk and Risk Analysis 47 3.1 Basic Ideas and Principles 47 3.1.1 Background Information 50 3.1.2 Models and Simplifications in Probability Considerations 51 3.1.3 Observable Quantities 51 3.2 Economic Risk 52 3.2.1 A Simple Cost Risk Example 52 3.2.2 Production Risk 55vi CONTENTS 3.2.3 Business and Project Management 57 3.2.4 Investing Money in a Stock Market 58 3.2.5 Discounted Cash Flow Analysis 59 3.3 Accident Risk 60 Bibliographic Notes 62 4 How to Assess Uncertainties and Specify Probabilities 63 4.1 What Is a Good Probability Assignment? 64 4.1.1 Criteria for Evaluating Probabilities 64 4.1.2 Heuristics and Biases 66 4.1.3 Evaluation of the Assessors 67 4.1.4 Standardization and Consensus 68 4.2 Modelling 68 4.2.1 Examples of Models 69 4.2.2 Discussion 70 4.3 Assessing Uncertainty of Y 71 4.3.1 Assignments Based on Classical Statistical Methods 72 4.3.2 Analyst Judgements Using All Sources of Information 73 4.3.3 Formal Expert Elicitation 74 4.3.4 Bayesian Analysis 75 4.4 Uncertainty Assessments of a Vector X 83 4.4.1 Cost Risk 83 4.4.2 Production Risk 85 4.4.3 Reliability Analysis 86 4.5 Discussion and Conclusions 90 Bibliographic Notes 92 5 How to Use Risk Analysis to Support Decision-Making 95 5.1 What Is a Good Decision? 96 5.1.1 Features of a Decision-Making Model 97 5.1.2 Decision-Support Tools 98 5.1.3 Discussion 103 5.2 Some Examples 106 5.2.1 Accident Risk 106 5.2.2 Scrap in Place or Complete Removal of Plant 108 5.2.3 Production System 113 5.2.4 Reliability Target 114 5.2.5 Health Risk 116 5.2.6 Warranties 119 5.2.7 Offshore Development Project 120 5.2.8 Risk Assessment: National Sector 122 5.2.9 Multi-Attribute Utility Example 124 5.3 Risk Problem Classification Schemes 127 5.3.1 A Scheme Based on Potential Consequences and Uncertainties 127 5.3.2 A Scheme Based on Closeness to Hazard and Level of Authority 131 Bibliographic Notes 142 6 Summary and Conclusions 145 Appendix A Basic Theory of Probability and Statistics 149 A.1 Probability Theory 149 A.1.1 Types of Probabilities 149 A.1.2 Probability Rules 151 A.1.3 Random Quantities (Random Variables) 155 A.1.4 Some Common Discrete Probability Distributions (Models) 159 A.1.5 Some Common Continuous Distributions (Models) 160 A.2.1 Non-Parametric Estimation 166 A.2.2 Estimation of Distribution Parameters 167 A.2.3 Testing Hypotheses 169 A.2.4 Regression 170 A.3 Bayesian Inference 171 A.3.1 Statistical (Bayesian) Decision Analysis 173 Bibliographic Notes 174 Appendix B Terminology 175 Bibliography 179 Index 187

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^{®}31-May-2018 17:16## Foundations of Risk Analysis

Language: english

Author: Terje Aven

Genre: Guide

Format: PDF/EPUB

Quality: Unknown

Pages count: 198

Description: Foundations of Risk Analysis

A Knowledge and Decision-Oriented Perspective

This book is about foundational issues in risk and risk analysis; how risk should be expressed; what the meaning of risk is; how to understand and use models; how to understand and address uncertainty; and how parametric probability models like the Poisson model should be understood and used. A unifying and holistic approach to risk and uncertainty is presented, for different applications and disciplines. Industry and business applications are highlighted, but aspects related to other areas are included. Decision situations covered include concept optimization and the need for measures to reduce risk for a production system, the choice between alternative investment projects and the use of a type of medical treatment.

Additional info: A.1.6 Some Remarks on Probability Models and Their

Parameters 164

A.1.7 Random Processes 165

A.2 Classical Statistical Inference 166

## Contents

Preface ix1 Introduction 1

1.1 The Importance of Risk and Uncertainty Assessments 1

1.2 The Need to Develop a Proper Risk Analysis Framework 4

Bibliographic Notes 6

2 Common Thinking about Risk and Risk Analysis 7

2.1 Accident Risk 7

2.1.1 Accident Statistics 7

2.1.2 Risk Analysis 11

2.1.3 Reliability Analysis 24

2.2 Economic Risk 28

2.2.1 General Definitions of Economic Risk in Business and

Project Management 28

2.2.2 A Cost Risk Analysis 30

2.2.3 Finance and Portfolio Theory 31

2.2.4 Treatment of Risk in Project Discounted Cash Flow

Analysis 34

2.3 Discussion and Conclusions 36

2.3.1 The Classical Approach 36

2.3.2 The Bayesian Paradigm 37

2.3.3 Economic Risk and Rational Decision-Making 39

2.3.4 Other Perspectives and Applications 40

2.3.5 Conclusions 42

Bibliographic Notes 43

3 How to Think about Risk and Risk Analysis 47

3.1 Basic Ideas and Principles 47

3.1.1 Background Information 50

3.1.2 Models and Simplifications in Probability Considerations 51

3.1.3 Observable Quantities 51

3.2 Economic Risk 52

3.2.1 A Simple Cost Risk Example 52

3.2.2 Production Risk 55vi CONTENTS

3.2.3 Business and Project Management 57

3.2.4 Investing Money in a Stock Market 58

3.2.5 Discounted Cash Flow Analysis 59

3.3 Accident Risk 60

Bibliographic Notes 62

4 How to Assess Uncertainties and Specify Probabilities 63

4.1 What Is a Good Probability Assignment? 64

4.1.1 Criteria for Evaluating Probabilities 64

4.1.2 Heuristics and Biases 66

4.1.3 Evaluation of the Assessors 67

4.1.4 Standardization and Consensus 68

4.2 Modelling 68

4.2.1 Examples of Models 69

4.2.2 Discussion 70

4.3 Assessing Uncertainty of Y 71

4.3.1 Assignments Based on Classical Statistical Methods 72

4.3.2 Analyst Judgements Using All Sources of Information 73

4.3.3 Formal Expert Elicitation 74

4.3.4 Bayesian Analysis 75

4.4 Uncertainty Assessments of a Vector X 83

4.4.1 Cost Risk 83

4.4.2 Production Risk 85

4.4.3 Reliability Analysis 86

4.5 Discussion and Conclusions 90

Bibliographic Notes 92

5 How to Use Risk Analysis to Support Decision-Making 95

5.1 What Is a Good Decision? 96

5.1.1 Features of a Decision-Making Model 97

5.1.2 Decision-Support Tools 98

5.1.3 Discussion 103

5.2 Some Examples 106

5.2.1 Accident Risk 106

5.2.2 Scrap in Place or Complete Removal of Plant 108

5.2.3 Production System 113

5.2.4 Reliability Target 114

5.2.5 Health Risk 116

5.2.6 Warranties 119

5.2.7 Offshore Development Project 120

5.2.8 Risk Assessment: National Sector 122

5.2.9 Multi-Attribute Utility Example 124

5.3 Risk Problem Classification Schemes 127

5.3.1 A Scheme Based on Potential Consequences and Uncertainties 127

5.3.2 A Scheme Based on Closeness to Hazard and Level of

Authority 131

Bibliographic Notes 142

6 Summary and Conclusions 145

Appendix A Basic Theory of Probability and Statistics 149

A.1 Probability Theory 149

A.1.1 Types of Probabilities 149

A.1.2 Probability Rules 151

A.1.3 Random Quantities (Random Variables) 155

A.1.4 Some Common Discrete Probability Distributions

(Models) 159

A.1.5 Some Common Continuous Distributions (Models) 160

A.2.1 Non-Parametric Estimation 166

A.2.2 Estimation of Distribution Parameters 167

A.2.3 Testing Hypotheses 169

A.2.4 Regression 170

A.3 Bayesian Inference 171

A.3.1 Statistical (Bayesian) Decision Analysis 173

Bibliographic Notes 174

Appendix B Terminology 175

Bibliography 179

Index 187

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