A cost estimate for a project such as the acquisition of a new aircraft or satellite system carries with it an inherent probability that the actual cost will exceed the estimate-that changes in requirements, technology, the economic environment, and a multitude of other factors that may occur over the life of the project will change the final cost. One major approach to cost risk analysis-the evaluating and quantifying of the uncertainty of a cost estimate-has been probabilistic: expressing the uncertainty in a cost estimate as a probability distribution over a range of potential costs. Cost analysts in industry and government and researchers in statistics and management have often proposed that, to get probability distributions for platforms using new and untried technologies, expert judgment should be tapped and subjective probability distributions elicited from the experts to represent cost uncertainty. This technical report reviews procedures for eliciting subjective probability distributions in cost risk analysis, both in the cost risk field and in other disciplines in which elicitation has been a topic of research-primarily, statistics and psychology. Because of a lack of empirical work in elicitation, especially in cost risk, the author also interviewed a number of senior people in the cost risk community, who gave insight into the practices of the field. This report should be of interest to cost analysis professionals who wish to quantify uncertainty when using expert opinions in cost risk analysis.

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.

Explores methods for the representation and treatment of uncertainty in risk assessment In providing guidance for practical decision-making situations concerning high-consequence technologies (e.g., nuclear, oil and gas, transport, etc.), the theories and methods studied in Uncertainty in Risk Assessment have wide-ranging applications from engineering and medicine to environmental impacts and natural disasters, security, and financial risk management. The main focus, however, is on engineering applications. While requiring some fundamental background in risk assessment, as well as a basic knowledge of probability theory and statistics, Uncertainty in Risk Assessment can be read profitably by a broad audience of professionals in the field, including researchers and graduate students on courses within risk analysis, statistics, engineering, and the physical sciences. Uncertainty in Risk Assessment: Illustrates the need for seeing beyond probability to represent uncertainties in risk assessment contexts. Provides simple explanations (supported by straightforward numerical examples) of the meaning of different types of probabilities, including interval probabilities, and the fundamentals of possibility theory and evidence theory. Offers guidance on when to use probability and when to use an alternative representation of uncertainty. Presents and discusses methods for the representation and characterization of uncertainty in risk assessment. Uses examples to clearly illustrate ideas and concepts.

The authors explain the ways in which uncertainty is an important factor in the problems of risk and policy analysis. This book outlines the source and nature of uncertainty, discusses techniques for obtaining and using expert judgment, and reviews a variety of simple and advanced methods for analyzing uncertainty.

Based on the author's 20 years of teaching, Risk Analysis in Engineering: Techniques, Tools, and Trends presents an engineering approach to probabilistic risk analysis (PRA). It emphasizes methods for comprehensive PRA studies, including techniques for risk management. The author assumes little or no prior knowledge of risk analysis on the p

The rise of the information age and the digital economy has dramatically changed engineering and other technology-driven fields. With tremendous advances in computing and communication systems, major organizational upheavals, all fueled by complexity, globalization, short cycle times, and lean supply chains, the functions of engineers have significantly changed. Engineers and similar professionals must be technically savvy and have product management and costing skills all while working in a distributed and often unstable environment. This new-edition textbook is updated to cover the integration of cost, risk, value, scheduling, and informationtechnologies going beyond basic engineering economics. Engineering Economics of Life Cycle Cost Analysis, Second Edition, offers a systems and life cycle or total ownership cost perspective. It presents advanced costing techniques such as simulation-based costing, decision and risk analysis, complex systemscosting, software, big data, and cloud computing estimation. Examples and problems demonstrating these techniques with real-world applications are also included. All engineers and similar professionals will find this book useful, but it is mainly written for systems engineers, engineering managers, program/product managers, and industrial engineers. The text can serve as a professional reference or for use with graduate courses on advanced engineering economic analysis and cost management, and financial analysis for engineers.