Abstract
Abstract Which symbols should be used to represent different groups of data in the same scatterplot? Hypotheses are derived to predict which symbol pairs should lead to good separability, based on the contrast of the symbols' visual properties or “features.” In two experiments, experimental scatterplots were shown to subjects on a computer screen; the dependent variable was the decision time to judge which of the two presented symbols was the more frequent one. Analyses of the within-subject effects yielded the following results: (1) Important feature contrasts are brightness, number of line endings, and curvature. (2) Symbols that differ simultaneously in two feature dimensions may be more separable than symbols that differ only in either one. (3) The contrasts between circular symbols and radial line symbols like the plus sign or the asterisk are excellent. Practical applications of these findings are discussed, as well as their contribution to the theory of visual perception.
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