BACKGROUND Bayesian statistics have become popular in the social sciences, in part because they are thought to present more useful information than traditional frequentist statistics. Unfortunately, little is known about whether or how interpretations of frequentist and Bayesian results differ. OBJECTIVES We test whether presenting Bayesian or frequentist results based on the same underlying data influences the decisions people made. RESEARCH DESIGN Participants were randomly assigned to read Bayesian and frequentist interpretations of hypothetical evaluations of new education technologies of various degrees of uncertainty, ranging from posterior probabilities of 99.8% to 52.9%, which have equivalent frequentist p values of .001 and .65, respectively. SUBJECTS Across three studies, 933 U.S. adults were recruited from Amazon Mechanical Turk. MEASURES The primary outcome was the proportion of participants who recommended adopting the new technology. We also measured respondents' certainty in their choice and (in Study 3) how easy it was to understand the results. RESULTS When presented with Bayesian results, participants were more likely to recommend switching to the new technology. This finding held across all degrees of uncertainty, but especially when the frequentist results reported a p value >.05. Those who recommended change based on Bayesian results were more certain about their choice. All respondents reported that the Bayesian display was easier to understand. CONCLUSIONS Presenting the same data in either frequentist or Bayesian terms can influence the decisions that people make. This finding highlights the importance of understanding the impact of the statistical results on how audiences interpret evaluation results.

中文翻译：

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代表数据说话：研究人员怎么说以及受众如何选择。

背景贝叶斯统计在社会科学中变得流行，部分是因为它们被认为比传统的常客统计提供了更多有用的信息。不幸的是，关于频率论和贝叶斯结果的解释是否或如何不同，我们知之甚少。目标我们测试基于相同的基础数据呈现贝叶斯或频率论结果是否会影响人们所做的决定。研究设计 参与者被随机分配阅读贝叶斯和频率论对各种不确定程度的新教育技术的假设评估的解释，后验概率为 99.8% 到 52.9%，频率论的等效 p 值分别为 0.001 和 0.65 . 主题 在三项研究中，从 Amazon Mechanical Turk 招募了 933 名美国成年人。措施 主要结果是建议采用新技术的参与者比例。我们还测量了受访者对他们选择的确定性以及（在研究 3 中）了解结果的难易程度。结果 当呈现贝叶斯结果时，参与者更有可能建议改用新技术。这一发现适用于所有程度的不确定性，尤其是当频率论结果报告 ap 值 >.05 时。那些根据贝叶斯结果推荐改变的人对他们的选择更加确定。所有受访者都表示贝叶斯显示更容易理解。结论 以频率论或贝叶斯术语呈现相同的数据会影响人们做出的决定。