University of California, Los Angeles, 502 Portola Plaza, Los Angeles, CA, 90095, USA.
Atten Percept Psychophys. 2021 Apr;83(3):1290-1311. doi: 10.3758/s13414-020-02212-x. Epub 2021 Jan 3.
In the age of big data, we are constantly inventing new data visualizations to consolidate massive amounts of numerical information into smaller and more digestible visual formats. These data visualizations use various visual features to convey quantitative information, such as spatial position in scatter plots, color saturation in heat maps, and area in dot maps. These data visualizations are typically composed of ensembles, or groups of related objects, that together convey information about a data set. Ensemble perception, or one's ability to perceive summary statistics from an ensemble, such as the mean, has been used as a foundation for understanding and explaining the effectiveness of certain data visualizations. However, research in data visualization has revealed some perceptual biases and conceptual difficulties people face when trying to utilize the information in these graphs. In this tutorial review, we will provide a broad overview of research conducted in ensemble perception, discuss how principles of ensemble encoding have been applied to the research in data visualization, and showcase the barriers graphs can pose to learning statistical concepts, using histograms as a specific example. The goal of this tutorial review is to highlight possible connections between three areas of research-ensemble perception, data visualization, and statistics education-and to encourage research in the practical applications of ensemble perception in solving real-world problems in statistics education.
在大数据时代，我们不断发明新的数据可视化方法，将大量的数值信息整合到更小、更易于理解的视觉格式中。这些数据可视化使用各种视觉特征来传达定量信息，例如散点图中的空间位置、热图中的颜色饱和度和点图中的面积。这些数据可视化通常由集合或相关对象的群组组成，它们共同传达有关数据集的信息。集合感知，即从集合中感知汇总统计信息（例如平均值）的能力，已被用作理解和解释某些数据可视化效果的基础。然而，数据可视化研究揭示了人们在尝试利用这些图形中的信息时面临的一些感知偏差和概念困难。在本教程综述中，我们将提供对集合感知研究的广泛概述，讨论集合编码原则如何应用于数据可视化研究，并展示图形可能对学习统计概念造成的障碍，以直方图为例。本教程综述的目的是强调集合感知、数据可视化和统计教育这三个研究领域之间的可能联系，并鼓励在统计教育中应用集合感知解决实际问题的实际应用研究。
