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A Science of Decision MakingThe Legacy of Ward Edwards$
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Jie W. Weiss and David J. Weiss

Print publication date: 2008

Print ISBN-13: 9780195322989

Published to Oxford Scholarship Online: January 2009

DOI: 10.1093/acprof:oso/9780195322989.001.0001

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Divide and Conquer: How to Use Likelihood and Value Judgments in Decision Making

Divide and Conquer: How to Use Likelihood and Value Judgments in Decision Making

Chapter:
(p.287) 23 Divide and Conquer: How to Use Likelihood and Value Judgments in Decision Making
Source:
A Science of Decision Making
Author(s):

Jie W Weiss

David J Weiss

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780195322989.003.0023

This chapter focuses on the concept of “divide and conquer” in decision analysis. The basic idea of “divide and conquer” consists of three steps. First, you take your cognitive, or your intellectual task, and break it up into little pieces along natural lines of cleavage. What those lines of cleavage will be depends on the nature of the task. Second, you make separate judgments about each of the pieces into which you fragmented the task. Third, you reaggregate the results of these judgments using an appropriate formal aggregation rule. Three different kinds of aggregation rules are relevant to these three different kinds of intellectual tasks. The aggregation rule that goes with diagnosis is Bayes's theorem of probability theory. The aggregation rule that goes with evaluation is nothing more complicated than the idea of weighted average. The aggregation rule that goes with decision-making is the idea of maximizing expected utility.

Keywords:   decision analysis, aggregation, divide and conquer, intellectual task, probability, weighted average

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