The authors investigated the degree of discounting and augmentation of a target cause by an alternative cause given a varying number of observations on the alternative cause while holding its degree of covariation constant. Two experiments showed that more observations of the alternative cause resulted in greater discounting or augmentation of a target cause. This sample size effect cannot be explained by current attribution theories based on statistical notions or belief updating but can be accounted for by a connectionist framework. In addition, the authors found that the sample size effect was stronger when the information was presented in a sequential trial-by-trial format as opposed to a summarized format but found no effect of information order. Possible extensions of statistical models with confidence weights that take account of sample size were considered and simulated but none accommodated the data as well as connectionist models.
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