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Exploring the Overestimation of Conjunctive Probabilities

机译:探索合取概率的高估

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People often overestimate probabilities of conjunctive events. The authors explored whether the accuracy of conjunctive probability estimates can be improved by increased experience with relevant constituent events and by using memory aids. The first experiment showed that increased experience with constituent events increased the correlation between the estimated and the objective conjunctive probabilities, but that it did not reduce overestimation of conjunctive probabilities. The second experiment showed that reducing cognitive load with memory aids for the constituent probabilities led to improved estimates of the conjunctive probabilities and to decreased overestimation of conjunctive probabilities. To explain the cognitive process underlying people’s probability estimates, the configural weighted average model was tested against the normative multiplicative model. The configural weighted average model generates conjunctive probabilities that systematically overestimate objective probabilities although the generated probabilities still correlate strongly with the objective probabilities. For the majority of participants this model was better than the multiplicative model in predicting the probability estimates. However, when memory aids were provided, the predictive accuracy of the multiplicative model increased. In sum, memory tools can improve people’s conjunctive probability estimates.
机译:人们通常会高估合并事件的可能性。作者探讨了联合概率估计的准确性是否可以通过增加有关相关事件的经验以及使用记忆辅助手段来提高。第一个实验表明,增加组成事件的经验会增加估计的和联合命中概率之间的相关性,但并不能减少联合命中率的高估。第二个实验表明,使用记忆辅助手段降低构成概率的认知负荷,可以改善对合取概率的估计,并减少对合取概率的过高估计。为了解释人们的概率估计所基于的认知过程,针对标准乘法模型对结构加权平均模型进行了测试。尽管生成的概率仍与目标概率密切相关,但配置加权平均模型生成的联合概率系统地高估了目标概率。对于大多数参与者而言,该模型在预测概率估计上要好于乘法模型。但是,当提供了记忆辅助工具时,乘法模型的预测准确性会提高。总之,记忆工具可以改善人们的联合概率估计。

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