Comparing averages in time series data

Authors:
Michael Correll;Danielle Albers;Steven Franconeri;Michael Gleicher
Affiliations:
University of Wisconsin - Madison, Madison, Wisconsin, United States;University of Wisconsin - Madison, Madison, WI, USA;Northwestern University, Evanston, IL, USA;University of Wisconsin - Madison, Madison, Madison, Wisconsin, United States
Venue:
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Year:
2012

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Abstract

Visualizations often seek to aid viewers in assessing the big picture in the data, that is, to make judgments about aggregate properties of the data. In this paper, we present an empirical study of a representative aggregate judgment task: finding regions of maximum average in a series. We show how a theory of perceptual averaging suggests a visual design other than the typically-used line graph. We describe an experiment that assesses participants' ability to estimate averages and make judgments based on these averages. The experiment confirms that this color encoding significantly outperforms the standard practice. The experiment also provides evidence for a perceptual averaging theory.