Abstract
Cleveland and McGill [10] concluded that dot plots are effective when one judges position along a common scale. We assessed the ability of graph readers to detect sample mean differences in multipanel dot plots. In Experiment 1, plots containing vertically arranged panels with different sample sizes and levels of variability were presented. Sensitivity was greater with large samples and low variability. In Experiment 2, sensitivity depended on the location of the comparison sample, with vertical and superimposed arrays yielding greater sensitivity than horizontal or diagonal arrays. Horizontal arrays also produced a bias to judge data in right-most panels as having higher means. Experiment 3 showed that ordering of data had little effect on sensitivity or bias. The results suggest that good graph design requires attention to how the specific features of a graphical format influence perceptual judgments of data
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Best, L.A., Smith, L.D., Stubbs, D.A. (2008). Detection of Sample Differences from Dot Plot Displays. In: Stapleton, G., Howse, J., Lee, J. (eds) Diagrammatic Representation and Inference. Diagrams 2008. Lecture Notes in Computer Science(), vol 5223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87730-1_27
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DOI: https://doi.org/10.1007/978-3-540-87730-1_27
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