Perception and Cognitive Implications of Logarithmic Scales for Exponentially Increasing Data: Perceptual Sensitivity Tested with Statistical Lineups
通过视觉推理实验，测试了线性尺度与对数尺度下人们检测指数增长数据差异的感知灵敏度，发现尺度选择对感知优势的影响取决于数据曲率。
Logarithmic transformations are a standard solution to displaying data that span several magnitudes within a single graph. This paper investigates the impact of log scales on perceptual sensitivity through a visual inference experiment using statistical lineups. Our study evaluated participant’s ability to detect differences between exponentially increasing data, characterized by varying levels of curvature, using both linear and logarithmic scales. Participants were presented with a series of plots and asked to identify the panel that appeared most different from the others. Due to the choice of scale altering the contextual appearance of the data, the results revealed slight perceptual advantages for both scales depending on the curvatures of the compared data. This study serves as the initial part of a three-paper series dedicated to understanding the perceptual and cognitive implications of using logarithmic scales for visualizing exponentially increasing data. These studies serve as an example of multi-modal graphical testing, examining different levels of engagement and interaction with graphics to establish nuanced and specific guidelines for graphical design.