<p>The inverse base-rate effect is the observation that on certain occasions people classify new objects as belonging to rare base-rate categories rather than common ones (e.g., D. L. Medin & S. M. Edelson, 1988). This finding is inconsistent with normative prescriptions of rationality, and provides an anomaly for current theories of human knowledge representation, such as the exemplar-based models of categorization, which predict a consistent use of base-rates (e.g., D. L. Medin & M. M. Schaffer, 1978). This thesis presents a novel explanation of the inverse base-rate effect. The proposal is that participants sometimes eliminate category options that are inconsistent with well-supported inference rules. These assumptions contrast with those by attentional theory (J. K. Kruschke, in press), according to which the inverse base-rate effect is the outcome of rapid attention shifts operating on cue-category associations. Study I, II, and III verified seven qualitative predictions derived from the eliminative inference idea. None of these phenomena can be explained by attentional theory. The most important of these findings were that elimination of well-known, common categories mediate the inverse base-rate effect rather than the strongest cue-category associations (Study I), that only participants with a rule-based mode of generalization exhibit the inverse base-rate effect (Study II), and that rapid attentional shifts per se do not accelerate learning, but rather decelerate it (Study III). In addition, Study I provided a quantitative implementation of the eliminative inference idea, ELMO, that demonstrated that this high-level reasoning process can produce the basic pattern of base-rate effects in the inverse base-rate design. Taken together, as an account of the inverse base-rate effect the empirical evidence of this thesis suggest that rule-based elimination is a powerful component of the inverse base-rate effect. But previous studies have indicated that attentional shifts affect the inverse base-rate effect, too. Therefore, a complete account of the inverse base-rate effect needs to integrate inductive and eliminative inferences operating on rule-based representations with attentional shifts. The Discussion of this thesis propose a number of suggestions for such integrative work. </p>

The inverse base-rate effect is the observation that on certain occasions people classify new objects as belonging to rare base-rate categories rather than common ones (e.g., D. L. Medin &amp; S. M. Edelson, 1988). This finding is inconsistent with normative prescriptions of rationality, and provides an anomaly for current theories of human knowledge representation, such as the exemplar-based models of categorization, which predict a consistent use of base-rates (e.g., D. L. Medin &amp; M. M. Schaffer, 1978). This thesis presents a novel explanation of the inverse base-rate effect. The proposal is that participants sometimes eliminate category options that are inconsistent with well-supported inference rules. These assumptions contrast with those by attentional theory (J. K. Kruschke, in press), according to which the inverse base-rate effect is the outcome of rapid attention shifts operating on cue-category associations. Study I, II, and III verified seven qualitative predictions derived from the eliminative inference idea. None of these phenomena can be explained by attentional theory. The most important of these findings were that elimination of well-known, common categories mediate the inverse base-rate effect rather than the strongest cue-category associations (Study I), that only participants with a rule-based mode of generalization exhibit the inverse base-rate effect (Study II), and that rapid attentional shifts per se do not accelerate learning, but rather decelerate it (Study III). In addition, Study I provided a quantitative implementation of the eliminative inference idea, ELMO, that demonstrated that this high-level reasoning process can produce the basic pattern of base-rate effects in the inverse base-rate design. Taken together, as an account of the inverse base-rate effect the empirical evidence of this thesis suggest that rule-based elimination is a powerful component of the inverse base-rate effect. But previous studies have indicated that attentional shifts affect the inverse base-rate effect, too. Therefore, a complete account of the inverse base-rate effect needs to integrate inductive and eliminative inferences operating on rule-based representations with attentional shifts. The Discussion of this thesis propose a number of suggestions for such integrative work.