The importance of the data-generating model in probability estimation☆
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Abstract When subjects appear to do poorly in a complex probability estimation task, they may be making careful estimates based on a different data-generating model than the one used by the experimenters. Eleven subjects estimated for 150 trials the probability that a dropped “bomb” had been aimed at one of two cities. Correlations between subjects' estimates and probabilities generated by the correct circular normal model and by a simple incorrect ratio of distances model showed six subjects using the wrong model with great accuracy. The usual analysis of such data, in which a possible confusion about the data-generation model is disregarded, would have led to the misleading conclusion that these subjects were very inaccurate at the task.
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