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Handbook of Decision Analysis by Eric R. Johnson, PhD, Steven N. Tani, PhD,, Terry Bresnick, MBA, Gregory S. Parnell, PhD

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CHAPTER TEN

Quantify Uncertainty

ERIC R. JOHNSON and STEVEN N. TANI

Do not expect to arrive at certainty in every subject which you pursue. There are a hundred things wherein we mortals … must be content with probability, where our best light and reasoning will reach no farther.

—Isaac Watts

10.1 Introduction
10.2 Structure the Problem in an Influence Diagram
10.3 Elicit and Document Assessments
10.3.1 Heuristics and Biases
10.3.2 Reference Events
10.3.3 Assessment Protocol
10.3.4 Assessing a Continuous Distribution
10.3.5 Conditioning Cases
10.3.6 The Reluctant Expert
10.4 Illustrative Examples
10.4.1 Geneptin
10.5 Summary
Key Terms
References

10.1 Introduction

Our aim is to help decision makers identify choices that can add substantial value when facing complex, uncertain, novel, high-stakes decision situations. Our decision analysis approach is to develop a composite perspective on how value is created based on the best available expertise, and to employ it in a value dialogue with experts, stakeholders, and decision makers aimed at providing insight to decision makers to aid their decision making.

We develop the composite perspective probabilistically, but not in the spirit of resignation indicated by the Isaac Watts quote above. Like Watts, we acknowledge that perfect knowledge is almost never available; but we rejoice in the availability of expertise, and set out to marshal it and bring it to bear on the decision problem at hand.

Previous chapters discuss framing and structuring ...

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