Insufficient Information To Assess Trustworthiness: Visualizations of Aggregates Rated Less Trustworthy than Visualizations of Individual Data

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 sinaplots, a data-showing alternative that displays individual observations within each category. In a preregistered online study (N = 162; Prolific), participants viewed two visualizations (bar chart and sinaplot) 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. Sinaplots were rated as more trustworthy than bar charts (d = 0.66), with 70% of participants favoring sinaplots versus 17% favoring bar charts; the effect remained substantial when restricted to the first graph viewed (d = 0.45). Qualitative analysis suggested that bar charts were frequently criticized as providing insufficient information to judge trustworthiness, whereas sinaplots more often elicited default trust. Together, these results suggest that showing individual data can increase perceived trustworthiness even while increasing visual density.