Discusses modeling cost uncertainty by the probability formalism and the Monte Carlo simulation method Demonstrates the key role of the central limit theorem in cost uncertainty analysis problems Presents unique statistical distributions not commonly found in the traditional literature, including the trapezoidal distribution, the bivariate normal-lognormal distribution, and the bivariate lognormal distribution Emphasizes the application of joint probability distributions for modeling cost-schedule uncertainty Develops probability distributions for a general form of the software cost-schedule model Illustrates the Mellin transform method for working with cost functions that are products, or quotients, of two or more random variables
A careful blend of theory and practice, this book presents a comprehensive approach to assessing the impact of unplanned events on the cost of engineering complex systems. It illustrates how probability theory is applied to model, measure, and manage risk in the cost of a systems engineering project. The book contains numerous mathematical and professional anecdotes, case studies, results, observations, and interpretations that clarify the challenges in cost risk analysis. It includes references, equations, and illustrations, provides theoretical and applied exercises, and uses examples and case discussions derived from systems engineering projects to describe key concepts.
Table of Contents
Uncertainty and the Role of Probability in Cost Analysis
Concepts of Probability Theory
Distributions and the Theory of Expectation
Special Distributions for Cost Uncertainty Analysis
Functions of Random Variables and Their Application to Cost Uncertainty Analysis
System Cost Uncertainty Analysis
Modeling Cost and Schedule Uncertainties-An Application of Joint Probability Theory
Epilogue: Considerations and Recommended Practices
Appendix A: Statistical Tables and Related Integrals
Appendix B: The Bivariate Normal-LogNormal Distribution
Appendix C: The Bivariate LogNormal Distribution
"Paul Garvey's new book belongs on the bookshelves of all persons responsible for providing cost estimates of futuristic, high-technology systems at various phases of development and production or for making decisions based on such cost estimates….[It] collects in one handy location all the probabilistic foundations of the new approach to cost estimating….Probability Methods for Cost Uncertainty Analysis will serve the system engineer and cost analyst as both a desk reference and, with its large volume of examples and exercises, a textbook for keeping up to speed (or getting up to speed) on these new procedures."
-Stephen A. Book, Ph.D., Distinguished Engineer, Systems Engineering Division, The Aerospace Corporation, Los Angeles, California
"Sound theoretical basis, fine-tuned by empirical evidence, and focused like a laser on the application of performing cost risk analysis on complex systems…after teaching from a collection of papers, I'm delighted to finally find this well-written text."
-Daryl J. Hauck, Ph.D.
Assistant Professor, Ohio
"…Paul Garvey has done a tremendous job taking a technical subject and producing a readable, interesting and informative primer. …strongly recommend[ed]…to all professional cost analysts, both for its readability and its insights....also recommend[ed] …to anyone who is in the position of making decisions based on cost estimates."
- Phalanx, The Bulletin of Military Operations Research
"...does a very thorough job of explaining probability methods in cost uncertainty analysis in mathematical terms."
- International Cost Engineering Council, 2001
"This book focuses on the development of a structured approach to quantifying the uncertainty of cost estimates, backed by a great deal of mathematical rigor."
- INCOSE Insight, 2001