Decision Analytica: An Example of Bayesian Inference and Decision Theory Using Mathematica

  • Robert J. Korsan


Decision analysis is a blending of four ingredients. First, subjective probability theory is used to describe a decision maker’s “a priori” uncertainty (degree of belief) about the outcomes of some event(s). Second, Bayesian inference is used to determine the appropriate “a posteriori” uncertainty given the revelation of some evidence. Third, utility theory is used to describe the decision maker’s values in a consistent, mathematically manipulable fashion. Fourth and finally, decision theory is used to determine the “optimal” strategy, i.e. the sequence of event-contingent actions which lead to the highest valued outcomes given the decision maker’s values.


Decision Maker Bayesian Inference Decision Theory Uncertain Variable Influence Diagram 
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© Springer Science+Business Media New York 1993

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  • Robert J. Korsan

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