We present a method for eliciting beliefs about probabilities when multiple realisations of an outcome are available, the “frequency” method. The method is applicable for any reasonable utility function. Unlike existing techniques that account for deviations from risk-neutrality, this method is highly transparent to subjects and easy to implement. Rather than identifying point beliefs these methods identify bounds on beliefs, thus trading off precision for generality and simplicity. An experimental comparison of this method and a popular alternative, the Karni method, shows that subjects indeed find the frequency method easier to understand. Significantly, we show that confusion due to the complexity of the Karni method leads to less cognitively able subjects erroneously stating a belief of 50%, a bias not present in the frequency method.

我们提出了一种在结果的多种实现可用时引发关于概率的信念的方法，即“频率”方法。该方法适用于任何合理的效用函数。与考虑偏离风险中性的现有技术不同，这种方法对受试者高度透明且易于实施。这些方法不是识别点信念，而是识别信念的界限，从而为通用性和简单性而牺牲精度。这种方法与流行的替代方法 Karni 方法的实验比较表明，受试者确实发现频率方法更容易理解。值得注意的是，我们表明，由于 Karni 方法的复杂性导致的混淆导致认知能力较差的受试者错误地陈述了 50% 的信念，这是频率方法中不存在的偏差。