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Cognitive biases are systematic errors in judgment. Researchers in datavisualizations have explored whether cognitive biases transfer todecision-making tasks with interactive data visualizations. At the same time,cognitive scientists have reinterpreted cognitive biases as the product ofresource-rational strategies under finite time and computational costs. In thispaper, we argue for the integration of resource-rational analysis throughconstrained Bayesian cognitive modeling to understand cognitive biases in datavisualizations. The benefit would be a more realistic "bounded rationality"representation of data visualization users and provides a research roadmap forstudying cognitive biases in data visualizations through a feedback loopbetween future experiments and theory

Using Resource-Rational Analysis to Understand Cognitive Biases in Interactive Data Visualizations