We conducted a series of three graphical studies to evaluate the impact displaying data on the log scale has on human perception of exponentially increasing trends compared to displaying data on the linear scale.
We developed and conducted a series of three graphical tests implemented through RShiny designed to evaluate the impact our choice of scale (log/linear) has on human perception of exponentially increasing trends.
Log scales are often used to display data over several orders of magnitude within one graph. Three graphical experimental tasks were conducted to evaluate the impact displaying data on the log scale has on human perception of exponentially increasing trends compared to displaying data on the linear scale. The results provide guidelines for readers to actively choose which of many possible graphics to draw in order to ensure their charts are effective at communicating the intended result.
We bring past graphical experiment studies into the modern era with r2d3, following a similar process to NYTimes You Draw It pages. In previous research, we conducted a graphical experimental task using lineups and visual inference to evaluate whether our ability to perceptually notice differences in exponentially increasing trends is impacted by the choice of scale. In the You Draw It experimental task, we focus on determining whether there are cognitive disadvantages to log scales by testing an individual's ability make predictions for exponentially increasing data.
We explored the use of linear and log scales to determine whether our ability to notice differences in exponentially increasing trends is impacted by the choice of scale. We conducted a visual inference experiment in which participants were shown a series of lineup plots and asked to identify the panel that was most different from the others. The use of visual inference to identify these guidelines suggests that there are perceptual advantages to log scales when differences are subtle.