Proceedings of the Annual Meeting of the Cognitive Science Society

Scientific results are often communicated with bar charts that display category means while omitting the underlying distribution of individual observations. Such visual simplification is commonly assumed to aid accessibility, yet direct evidence about how this design choice affects perceived trustworthiness is limited. We compared initial trustworthiness judgments for average-only bar charts versus sina plots, a data-showing alternative that displays individual observations within each category (Sidiropoulos et al., 2018). In a preregistered online study (N = 162; Prolific), participants viewed two visualizations (bar chart and sina plot) of the same textbook-sourced scientific result (order randomized), completed graph-reading estimates, rated each graph's trustworthiness on a 0–100 scale, rated six antecedents of trustworthiness (e.g., accuracy, completeness, bias), and provided free-response justifications. Sina plots were rated as more trustworthy than bar charts (d = .66), with 70% of participants favoring sina plots versus 17% favoring bar charts; the effect remained substantial when restricted to the first graph viewed (d = .45). Qualitative analysis suggested that bar charts were frequently criticized as providing insufficient information to judge trustworthiness, whereas sina plots more often elicited default trust. Together, these results suggest that showing individual data points can increase perceived trustworthiness even while increasing visual density.