Entire disciplines are dedicated to separately exploring the relationship between sensation and perception; attention and learning; and information access and decision making. This work aims to bridge these fields though studies of data visualizations and decision making. A data visualization communicates information about synthesized data points for an observer. For graphical communication to work, all parties involved must understand regularities in the representations that are being used. Extracting regularities from observations is in the category learning wheelhouse, and so methods and findings from categorization literature are used to inform this work. Through the following experiments, the perception of multivariate data via visualization is explored. The framework for this exploration is an extension of existing proposals for a science of data visualization. The present work extends existing proposals by adding decision making as a critical element for a science of visualization. It’s great to understand how people can read a graph, but it’s even more informative to understand how that reading influences their actions.
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Thesis advisor: Blair, Mark
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