‘Attentional Bias’ in correlation judgments? Smedslund (1963) revisited

Smedslund (1963) reports one of the first studies that investigated human judgments of correlation. Smedslund’s conclusion, that people reason about correlation mostly from a consideration of the number of times two variables co‐occur, has become textbook wisdom (e.g. Baron’s "attentional bias", 1994). Yet the data reported in Smedslund’s paper fall short of endorsing such a conclusion. After reviewing the original paper, we present the method with which we replicated Smedslund’s main experiment. In Experiment 1 subjects were presented with symptom‐disease correlation data through a simulated medical diagnosis task. Subjects clearly discriminated between data sets which shared an equal number of symptom‐disease co‐occurrences but which otherwise showed different levels of correlation. Subjects’ diagnoses showed a propensity to predict the disease in the presence of the symptom, and symptom‐disease co‐occurrences were overestimated in two of the five data sets presented to the subjects. Experiment 2 used a novel abstract scenario with a symmetric predictor variable. Judgments again indicated good discrimination, and biases in prediction responses and case recall were eliminated. In both experiments, judgments of zero correlation were a function of the outcome base rate. We evaluate and contrast the extent to which Cheng’s (1997) model of causal induction and two associative models, Rescorla and Wagner (1972) and Pearce (1987) can anticipate the observed pattern in the mean judgments.