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变异性导致平均值摘要的高估。

Variability leads to overestimation of mean summaries.

机构信息

Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.

Department of Humanities, New Jersey Institute of Technology, Newark, NJ, USA.

出版信息

Atten Percept Psychophys. 2021 Apr;83(3):1129-1140. doi: 10.3758/s13414-021-02269-2. Epub 2021 Mar 26.

Abstract

Research on ensemble perception has shown that people can extract both mean and variance information, but much less is understand how these two different types of summaries interact with one another. Some research has argued that people are more erroneous in extracting the mean of displays that have greater variability. In all three experiments, we manipulated the variability in the displays. Participants reported the mean size of a set of circles (Experiment 1) and mean length of horizontally placed (Experiment 2a) and randomly oriented lines (Experiment 2b). In all experiments, we found that mean size estimations were more erroneous for higher than smaller variance displays. More critically, there was a tendency to overestimate the mean, driven by variance in both task-relevant and task-irrelevant features. We discuss these findings in relation to limitations in concurrent summarization ability and outlier discounting in ensemble perception.

摘要

集合感知研究表明,人们可以提取均值和方差信息,但对于这两种不同类型的摘要如何相互作用,人们的了解要少得多。一些研究认为,人们在提取具有更大变异性的显示的均值时更容易出错。在所有三个实验中,我们都操纵了显示的可变性。参与者报告了一组圆形(实验 1)、水平放置(实验 2a)和随机定向线(实验 2b)的平均长度。在所有实验中,我们发现均值估计对于更高方差的显示比更小方差的显示更容易出错。更重要的是,存在一种由任务相关和任务无关特征的方差驱动的高估均值的趋势。我们将这些发现与集合感知中并发摘要能力和异常值折扣的局限性联系起来进行了讨论。

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