Conceptualizing, Explaining, and Improving Accuracy: Process Models of Probability Judgment

Abstract

The present article argues for the importance of accurate probability judgments as a foundation for good decision making. It begins with a review of evidence about how laypersons — everyday decision makers — conceptualize what it means for probability judgments to be accurate or inaccurate. It then sketches key formal notions of probability judgment accuracy (e.g., calibration) that guide current scholarly work on the subject. The remaining parts of the article review studies demonstrating how the accuracy dimensions distinguished in formal analyses have led to useful insights into the processes by which people actually arrive at probability judgments that are either strong or weak in particular respects. Implications for how judgments, and hence decisions, might be improved are discussed throughout.