This paper aims to investigate the mathematical problem-solving capabilities
of Chat Generative Pre-Trained Transformer (ChatGPT) in case of Bayesian
reasoning. The study draws inspiration from Zhu & Gigerenzer's research in
2006, which posed the question: Can children reason the Bayesian way? In the
pursuit of answering this question, a set of 10 Bayesian reasoning problems
were presented. The results of their work revealed that children's ability to
reason effectively using Bayesian principles is contingent upon a
well-structured information representation. In this paper, we present the same
set of 10 Bayesian reasoning problems to ChatGPT. Remarkably, the results
demonstrate that ChatGPT provides the right solutions to all problems.

本研究旨在探究 ChatGPT 在贝叶斯推理中的数学问题解决能力。研究灵感源自 2006 年 Zhu 和 Gigerenzer 的研究，提出了一个问题：儿童能以贝叶斯方式进行推理吗？通过一组 10 个贝叶斯推理问题的实验，结果揭示了儿童有效运用贝叶斯原理进行推理的能力取决于信息的良好结构化表示。本文将同样的一组 10 个贝叶斯推理问题提供给 ChatGPT，结果显示 ChatGPT 能够给出所有问题的正确解答。