Statistical Laws of Confidence Versus Behavioral Response: How Individuals Respond to Public Management Decisions Under Uncertainty

Abstract

Rational policy analysis confronts the problem of uncertainty directly through various methods of quantification. This paper considers the extent to which individuals are able to subjectively apply the basic tenets of inferential statistics surrounding the generation, use, and interpretation of prediction and confidence intervals. In a small-group experiment, subjects successfully internalized the tradeoff between an interval's accuracy and its sensitivity or width. Unfortunately, subjects could not calibrate the magnitude of the interval based on empirical information about underlying uncertainty (i.e., variance) in the phenomena being estimated. The results, consistent with much of the cognitive psychological research, suggest human judgment needs external calibration to successfully incorporate uncertainty into decisionmaking.

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