School of Computer Science, University College Dublin, Ireland.
Cogn Psychol. 2020 Dec;123:101306. doi: 10.1016/j.cogpsych.2020.101306. Epub 2020 Nov 11.
A number of recent theories have suggested that the various systematic biases and fallacies seen in people's probabilistic reasoning may arise purely as a consequence of random variation in the reasoning process. The underlying argument, in these theories, is that random variation has systematic regressive effects, so producing the observed patterns of bias. These theories typically take this random variation as a given, and assume that the degree of random variation in probabilistic reasoning is sufficiently large to account for observed patterns of fallacy and bias; there has been very little research directly examining the character of random variation in people's probabilistic judgement. We describe 4 experiments investigating the degree, level, and characteristic properties of random variation in people's probability judgement. We show that the degree of variance is easily large enough to account for the occurrence of two central fallacies in probabilistic reasoning (the conjunction fallacy and the disjunction fallacy), and that level of variance is a reliable predictor of the occurrence of these fallacies. We also show that random variance in people's probabilistic judgement follows a particular mathematical model from frequentist probability theory: the binomial proportion distribution. This result supports a model in which people reason about probabilities in a way that follows frequentist probability theory but is subject to random variation or noise.
一些最近的理论表明，人们在概率推理中所看到的各种系统偏差和谬误可能纯粹是推理过程中随机变异的结果。在这些理论中，基本论点是随机变异具有系统的回归效应，从而产生了观察到的偏差模式。这些理论通常将这种随机变异视为给定的，并假设概率推理中的随机变异程度足够大，可以解释观察到的谬误和偏差模式；很少有研究直接检验人们概率判断中随机变异的特征。我们描述了 4 项实验，研究了人们概率判断中随机变异的程度、水平和特征属性。我们表明，方差的程度很容易大到足以解释概率推理中两个中心谬误的发生（合取谬误和析取谬误），并且方差的水平是这些谬误发生的可靠预测指标。我们还表明，人们概率判断中的随机变异遵循来自频率论概率论的特定数学模型：二项式比例分布。这一结果支持了一种模型，即在概率推理中，人们的推理方式遵循频率论概率论，但受到随机变异或噪声的影响。
