Hypothesis Generation and Plausibility Assessment.

Abstract

A hypothesis generation model is described which consists of two sub-processes. Hypotheses are retrieved from memory using several data as retrieval cues in the hypothesis retrieval sub-process. These hypotheses are then evaluated by a plausibility assessment sub-process. Two experiments are described. A memory retrieval experiment examined hypothesis retrieval from memory using multiple data. A memory-tagging model is described which predicts the probability of multi-data hypothesis retrieval. Performance in this task was poor; subjects rarely generated an adequate hypothesis set. A second plausibility assessment experiment was performed where subjects estimated the plausibility of specified hypotheses using varying amounts of data. Plausibility assessments for specified hypotheses were usually extreme in comparison to the posterior odds calculated by Bayes' theorem. This result was also attributed to deficiencies in hypothesis retrieval from memory. (Author)