School of Health Information Sciences, University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Psychol Rev. 2010 Apr;117(2):697-705; discussion 706-11. doi: 10.1037/a0018994.
On the basis of the statistical concept of waiting time and on computer simulations of the "probabilities of nonoccurrence" (p. 457) for random sequences, Hahn and Warren (2009) proposed that given people's experience of a finite data stream from the environment, the gambler's fallacy is not as gross an error as it might seem. We deal with two critical issues in Hahn and Warren's argument, a possible ambiguity in distinguishing the events of occurrence and nonoccurrence, and an incomplete consideration of the context in which the statistics of waiting time are defined. Our analyses show that the statistics of waiting time and the probabilities of nonoccurrence, once correctly interpreted, do not vindicate the error in the gambler's fallacy.
基于等待时间的统计概念,以及对随机序列“不发生概率”(第 457 页)的计算机模拟,Hahn 和 Warren(2009)提出,鉴于人们从环境中获得的有限数据流的经验,赌徒谬误并不像表面上看起来那样是一个严重的错误。我们讨论了 Hahn 和 Warren 论点中的两个关键问题,即区分发生和不发生事件时可能存在的歧义,以及在定义等待时间统计数据的上下文中考虑不完整。我们的分析表明,一旦正确解释了等待时间的统计数据和不发生的概率,就不能证明赌徒谬误中的错误。