Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 Recent Milestones
- 3 An Overview of Quantitative Policy Analysis
- 4 The Nature and Sources of Uncertainty
- 5 Probability Distributions and Statistical Estimation
- 6 Human Judgment about and with Uncertainty
- 7 Performing Probability Assessment
- 8 The Propagation and Analysis of Uncertainty
- 9 The Graphic Communication of Uncertainty
- 10 Analytical A Software Tool for Uncertainty Analysis and Model Communication
- 11 Large and Complex Models
- 12 The Value of Knowing How Little You Know
- Index
10 - Analytical A Software Tool for Uncertainty Analysis and Model Communication
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 Recent Milestones
- 3 An Overview of Quantitative Policy Analysis
- 4 The Nature and Sources of Uncertainty
- 5 Probability Distributions and Statistical Estimation
- 6 Human Judgment about and with Uncertainty
- 7 Performing Probability Assessment
- 8 The Propagation and Analysis of Uncertainty
- 9 The Graphic Communication of Uncertainty
- 10 Analytical A Software Tool for Uncertainty Analysis and Model Communication
- 11 Large and Complex Models
- 12 The Value of Knowing How Little You Know
- Index
Summary
“The real value of computers is for communication, not computation.”
Natasha KalatinIt goes almost without saying that doing quantitative analysis means creating computer models, especially if you want to treat the uncertainty explicitly. It is possible to do back-of-the-envelope calculations for a handful of variables with pencil and paper, using simple error-propagation methods (Section 8.3.5) or probability trees (Section 8.4). Indeed, that is an excellent way to develop your intuitions when you start a project. Any serious uncertainty analysis, however, requires a computer. Fortunately, there are several commercially available software products that make the probabilistic treatment of uncertainty quite straightforward. These tools obviate the need for the analyst to master the intricacies of implementing complicated Monte Carlo codes.
How should we choose and use software for quantitative modeling and risk analysis? At first blush, you might think that quantitative modeling — especially when it treats uncertainty — is primarily a matter of number crunching. Certainly, that is a critical part of it; but if the ultimate purpose of the computation is improved insight into complicated situations, and enhanced understanding of the risks and opportunities, then modeling comprises a great deal more. The treatment of uncertainty (the primary focus of this book) is only one of many objectives.
In Chapter 3, we discussed the goals and motivations for risk and policy analysis, culminating in our suggested “ten commandments for good policy analysis” (Section 3.8).
- Type
- Chapter
- Information
- UncertaintyA Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis, pp. 257 - 288Publisher: Cambridge University PressPrint publication year: 1990
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