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图形不会引导人们从相关性推断因果关系。

Graphs do not lead people to infer causation from correlation.

机构信息

Department of Psychology.

出版信息

J Exp Psychol Appl. 2022 Jun;28(2):314-328. doi: 10.1037/xap0000393. Epub 2022 Feb 28.

Abstract

Media articles often communicate the latest scientific findings, and readers must evaluate the evidence and consider its potential implications. Prior work has found that the inclusion of graphs makes messages about scientific data more persuasive (Tal & Wansink, 2016). One explanation for this finding is that such visualizations evoke the notion of "science"; however, results are mixed. In the current investigation we extend this work by examining whether graphs lead people to erroneously infer causation from correlational data. In two experiments we gave participants realistic online news articles in which they were asked to evaluate the research and apply the work's findings to a real-life hypothetical scenario. Participants were assigned to read the text of the article alone or with an accompanying line or bar graph. We found no evidence that the presence of graphs affected participants' evaluations of correlational data as causal. Given that these findings were unexpected, we attempted to directly replicate a well-cited article making the claim that graphs are persuasive (Tal & Wansink, 2016), but we were unsuccessful. Overall, our results suggest that the mere presence of graphs does not necessarily increase the likelihood that one infers incorrect causal claims. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

摘要

媒体文章经常传播最新的科学发现,读者必须评估证据并考虑其潜在影响。先前的研究发现,图形的加入使有关科学数据的信息更具说服力(Tal & Wansink,2016)。对此发现的一种解释是,这种可视化唤起了“科学”的概念;然而,结果喜忧参半。在当前的研究中,我们通过研究图形是否会导致人们错误地从相关数据推断因果关系来扩展这项工作。在两项实验中,我们给参与者提供了真实的在线新闻文章,要求他们评估研究并将研究结果应用于现实生活中的假设情景。参与者被分配单独阅读文章的文本或带有伴随的线图或条形图。我们没有发现图形的存在会影响参与者对相关数据的因果关系评估的证据。鉴于这些发现出人意料,我们试图直接复制一篇引用率很高的文章,该文章声称图形具有说服力(Tal & Wansink,2016),但我们没有成功。总的来说,我们的结果表明,图形的存在并不一定会增加人们推断错误因果关系的可能性。(PsycInfo 数据库记录(c)2022 APA,保留所有权利)。

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