Uncertainty in Risk Assessment

<p><b>Explores methods for the representation and treatment of uncertainty in risk assessment</b></p> <p>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 <i>Uncertainty in Risk Assessment</i> 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.</p> <p>While requiring some fundamental background in risk assessment, as well as a basic knowledge of probability theory and statistics, <i>Uncertainty in Risk Assessment</i> 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.</p> <p><i>Uncertainty in Risk Assessment</i>:</p> <ul> <li>Illustrates the need for seeing beyond probability to represent uncertainties in risk assessment contexts.</li> <li>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.</li> <li>Offers guidance on when to use probability and when to use an alternative representation of uncertainty.</li> <li>Presents and discusses methods for the representation and characterization of uncertainty in risk assessment.</li> <li>Uses examples to clearly illustrate ideas and concepts.</li> </ul>