This text presents notions and ideas at the foundations of a statistical treatment of risks. The focus is on statistical applications within the field of engineering risk and safety analysis. Coverage includes Bayesian methods. Such knowledge facilitates the understanding of the influence of random phenomena and gives a deeper understanding of the role of probability in risk analysis. The text is written for students who have studied elementary undergraduate courses in engineering mathematics, perhaps including a minor course in statistics. This book differs from typical textbooks in its verbal approach to many explanations and examples.

A graduate level textbook on probabilistic risk analysis, aimed at statisticians, operations researchers and engineers.

In recent years public attention has focused on an array of low-probability/high-consequence (LC/HC) events that pose a signif icant threat to human health, safety, and the environment. At the same time, public and private sector responsibilities for the assessment and management of such events have grown because of a perceived need to anticipate, prevent, or reduce the risks. In attempting to meet these responsibilities, legislative, judicial, regulatory, and private sector institutions have had to deal with the extraordinarily complex problem of assessing and balancing LP/ HC risks against the costs and ben if its of risk reduction. The need to help society cope with LP/HC events such as nuclear power plant accidents, toxic spills, chemical plant explosions, and transportation accidents has given rise to the development of a new intellectual endeavor: LP/HC risk analysis. The scope and complexity of these analyses require a high degree of cooperative effort on the part of specialists from many f~elds. Analyzing technical, social, and value issues requires the efforts of physicists, biologists, geneticists, statisticians, chemists, engineers, political scientists, sociologists, decision analysts, management scientists, economists, psychologists, ethicists, lawyers, and policy analysts. Included in this volume are papers by authors in each of these disciplines. The papers share in common a focus on one or more of the following questions that are generic to the analysis of LP/HC risks.

A Training Tool for the Environmental Risk ProfessionalEnvironmental Risk Analysis: Probability Distribution Calculations defines the role that probability distributions play in risk analysis, and gives direction on how to measure and compare the magnitude of risk more efficiently. Designed for the practicing environmental engineer and scientist, t

The objective of Risk Analysis in Theory and Practice is to present this analytical framework and to illustrate how it can be used in the investigation of economic decisions under risk. In a sense, the economics of risk is a difficult subject: it involves understanding human decisions in the absence of perfect information. How do we make decisions when we do not know some of events affecting us? The complexities of our uncertain world and of how humans obtain and process information make this difficult. In spite of these difficulties, much progress has been made. First, probability theory is the corner stone of risk assessment. This allows us to measure risk in a fashion that can be communicated among decision makers or researchers. Second, risk preferences are now better understood. This provides useful insights into the economic rationality of decision making under uncertainty. Third, over the last decades, good insights have been developed about the value of information. This helps better understand the role of information in human decision making and this book provides a systematic treatment of these issues in the context of both private and public decisions under uncertainty. Balanced treatment of conceptual models and applied analysis Considers both private and public decisions under uncertainty Website presents application exercises in Excel

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.