Caption: Bayesian posteriors of accuracy as determined by SD Pairs, and Visual Interventions (colors). Rectangular connectors indicate comparisons where the credible interval do not include zero within and across SD Pairs and Visual Interventions.

Caption: Bayesian posteriors of accuracy as determined by scaling of PDF plots (rows) and visual interventions (colors).It All Begins Here

Caption: Percent of each visualization that led to each strategy (columns) across tested visualizations (rows). Strategies are not mutually exclusive so rows and columns may not equal 100%.

Caption: Conditional effects for graph literacy in Exp. 1. Darker lines show means, color bands show 95% CIs.

Caption: Croissant charts’ intended affordances. PDF shape for expressiveness. Minimal slices with gaps afford continuity and parts of a whole. Dots afford counting and equality across slices.

In-line figures for illustrative purposes.

Caption: QDPs’ afforded mental actions from our pilot study.

Caption: Correct visual strategies for comparing cumulative probabilities of two PDFs. Left: Equal-area PDF plots can be compared via a single area comparison. Right: Equal-height PDF plots must be compared via a proportional area comparison.

Caption: Workflow for examining and re-designing a visualization using cognitive affordances. In steps 1 and 2, a designer populates the cognitive affordance framework with their communication goals and target audience. In step 3, the designer uses investigative methods or past research to determine what their current visualization affords. In step 4, the designer identifies undesired information that their visualization communicates and uses cognitive affordances to trace the information back to root design decisions. In step 5, the designer uses cognitive affordances to hypothesize about the likely communication of alternate design decisions. In step 6, the designer implements visualization redesigns using step 5’s identified encodings.