Review of Decisions under Uncertainty by Ian Jordaan

Ross B. Corotis University of Colorado at Boulder. E-mail: Corotis@colorado.edu This book takes a very interesting approach to the treatment of uncertainty and its role in decision making. The author, who has extensive background in both academia and industry, uses an intuitive argument whenever possible to derive common laws of probability. As such, he intends the book as “an introduction to probability for engineers” quoted from the Preface , and appropriate for use in an engineering curriculum; exercises are included at the end of each chapter. This approach has a distinct advantage for such use in contrast to the more traditional mathematical foundation, from which most engineering students are discouraged by a perceived lack of applicability. Based on the author’s experience, it seems that the book would fit best into an undergraduate civil engineering curriculum, since applications are focused on decisions for the built environment. How the book fares in comparison to the two common probability texts oriented toward civil engineers, Probability, Statistics and Decision, by Jack Benjamin and Allin Cornell and Probability Concepts in Engineering Planning and Design, by Alfredo Ang and Wilson Tang, is unclear. Since these latter two were written about 3 decades ago, Jordaan’s book starts off with the advantage of current examples. Several of the topics in the book are normally considered only at the graduate level of engineering education spectral analysis of random processes, optimization theory, and extreme value theory, etc. , and the inclusion of these may make the book somewhat daunting to undergraduate students. The stated goal that the book “will be of use to practicing engineers” is probably one more of hope than reality since the mathematics and details of examples quickly moves beyond the interest level of most professionals looking for answers. For instance, the book makes the argument that “... probability is not a frequency... We use frequencies to estimate probabilities; this distinction is important.” This may be true, but the importance and subtlety of the distinction is not expected to capture the attention and interest of practicing engineers. This book encompasses a much broader array of topics than is typically covered in a single-semester course. In addition to traditional probability theory, it has extensive coverage of utility theory, which the author states is as fundamental as probability theory in the process of decision making he refers to them as being “related dually” . The author also denotes significant space throughout the book to formal consideration of Bayesian methods, based on his evaluation that engineers are continually faced with the prospect of new information, which should be incorporated into their decision process. It remains to be seen whether the breadth of topics, including entropy and optimization, decreases the depth of coverage of more traditional probabilistic and statistical concepts to the point where students will find the concepts somewhat difficult to follow. Chapter one, entitled “Uncertainty and decision-making,” provides a very nice overview of the role of probability analysis in