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Frequency vs. Probability Formats: Framing the Three Doors Problem

机译:频率与概率格式:构筑三门问题

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摘要

Instead of subscribing to the view that people are unable to perform Bayesian probabilistic inference, recent research suggests that the algorithms people naturally use to perform Bayesian inference are better adapted for information presented in a natural frequency format than in the common probability format. We tested this hypothesis on the notoriously difficult three doors problem, inducing subjects to consider the likelihoods involved in terms of natural frequencies or in terms of probabilities. We then examined their ability to perform the mathematics underlying the problem, a stronger indication of Bayesian inferential performance than merely whether they gave the correct answer to the problem. With a robustness that may surprise people unfamiliar with the effects of information formats, the natural frequency group demonstrated dramatically greater normative mathematical performance than the probability group. This supports the importance of information formats in a more complex context than in previous studies.
机译:最近的研究表明,人们自然地用来执行贝叶斯推理的算法比使用普通概率格式更好地适应了以自然频率格式表示的信息,而不是遵循人们无法执行贝叶斯概率推理的观点。我们在一个非常困难的三门问题上检验了这个假设,促使受试者考虑以自然频率或概率来考虑的可能性。然后,我们检查了他们执行问题背后数学的能力,这不仅仅是他们是否给出了正确答案的证据,更能说明贝叶斯推理能力。由于固有的健壮性可能会让不熟悉信息格式影响的人感到惊讶,因此自然频率组显示出比概率组大得多的标准数学性能。与以前的研究相比,这在更复杂的情况下支持了信息格式的重要性。

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