明确嵌套集合关系对贝叶斯推理的促进效应

Facilitating Effect of Transparent Netsted-Sets Relations on Bayesian Reasoning

以经典的乳癌问题作为实验任务，通过两个实验分别探讨了有助于明确嵌套集合关系的逐步提问、树图表征等外商表征方式以及元认知调探和被式类型等因素对贝叶斯推理的影响。结果发现：（1）逐歩提问对改善贝叶斯推理的成绩没有显著作用；（2）完整和不完整的树图表征显著地促进了推理成绩，但简约的树图表征的促进作用不显著；（3）叙述理由引发的元认知监控显著地促进了推理成绩；（4）文科和理科两组被试的推理成绩没有显著差异。

The natural frequency hypothesis proposed by Gigerenzer & Hoffrage（1995）assumed that the cognitive fallacy in Bayesian inference would be diminished when the problem was presented in frequency format instead of in probability format. The nested-sets hypothesis proposed by Mellers et al. （1999）， however， thought that the natural frequency format facilitated the problem solving because this format made the visualization of the nested relation among sets. Sloman （2003） and Gigerenzer & Hoffrage（1999） explained the facilitating effect of frequency format on problem-solving from the point of view of the concept of set. On the basis of the findings above， this study aimed to evaluate the effects of different external representation on transparent nested-sets relation， and to discuss the facilitating effect of transparent nested-sets relations on Bayesian inference. In addition， this study investigated if transparent nested-sets relations could diminish the difference on reasoning results form participants who are majored in arts or science. The present study also discussed if narrating reason could enhance participants’ meta-cognition monitoring and understanding of the nested relation in classic Bayesian inference， thereby improve their reasoning results.