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Eliciting and Analyzing Expert Judgment: A Practical Guide (ASA-SIAM Series on Statistics and Applied Probability)Eliciting and Analyzing Expert Judgment: A Practical Guide (ASA-SIAM Series on Statistics and Applied Probability)Mary A. Meyer, Jane M. BookerExpert judgment is invaluable for assessing products, systems, and situations for which measurements or test results are sparse or nonexistent. Eliciting and Analyzing Expert Judgment: A Practical Guide takes the reader step by step through the techniques of eliciting and analyzing expert judgment, with special attention given to helping the reader develop elicitation methods and tools adaptable to a variety of unique situations and work areas.
The analysis procedures presented in the book may require a basic understanding of statistics and probabilities, but the authors have provided detailed explanations of the techniques used and have taken special care to define all statistical jargon. Originally published in 1991, this book is designed so that those familiar with the use of expert judgment can quickly find the material appropriate for their advanced background. Newcomers will be eased into the topic by special chapters explaining what expert judgment is and how it can be used, an introduction to statistical techniques and notation, definitions for statistical terms, and a separate glossary of expert judgment terms. People in industry, government, and academia are aware that they must capture their expertise, as well as access and update it in electronic repositories (knowledge systems), if they are to preserve their chief assets and competitive edge. This book provides a shortcut to creating these knowledge systems. The innovative methodology PREDICT (Performance and Reliability Evaluation from Diverse Information, Combination, and Tracking) is used to predict the performance of a complex system undergoing change. This book provides PREDICT users with guidance on how to elicit and analyze expert judgment, including the associated uncertainty. Expert judgment is an important source of information when test data is not available. Audience
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