Averaging Rules and Adjustment Processes: The Role of Averaging in Inference

摘要

Two empirically well supported research findings in the judgment literature are that (1) human judgments often appear to follow an averaging rule, and (2) judgments in Bayesian inference tasks are usually conservative relative to optimal judgments. This paper argues that both averaging and conservatism in the Bayesian task occur because subjects produce their judgments by using an adjustment strategy that is qualitatively equivalent to averaging. Two experiments are presented that support this view by showing qualitative errors in the direction of revisions in the Bayesian task that are well-accounted for by the simple adjustment strategy. Two additional results are also discussed: (1) a tendency for subjects in one experiment to evaluate sample evidence according to representativeness rather than according to relative likelihood, and (2) a strong recency effect that may reflect the influence of the internal representation of sample information during the judgment process. (Author)