HEURISTICS AND BIASES IN THE EYEBALLING OF DATA - THE EFFECTS OF CONTEXT ON INTUITIVE CORRELATION ASSESSMENT

For a wide variety of real-world decisions, people must examine numeri cal tables and intuitively assess the correlations that exist among me aningful variables. The normative properties of correlation coefficien ts suggest that such decisions should be unaffected by perceptual fact ors (e.g., changes in row and column locations), semantic factors (e.g ., the referents of the numbers), or certain transformations of the va riables (e.g., adding a constant or multiplying by a constant). Four e xperiments demonstrated that judgments based on perceived correlations violate these normative properties. A general model of intuitive cova riation assessment was proposed to explain the observed biases. Estima tion of this model at the aggregate and individual levels suggested th at no single heuristic is consistent with all of the results. Instead, the existence of several qualitatively different types of heuristics was supported. The distribution of individual-level decision rules acr oss types of heuristics was systematically related to contextual facto rs.