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research-article

Comparing averages in time series data

Authors:

Michael Correll,

Danielle Albers,

Steven Franconeri,

Michael GleicherAuthors Info & Claims

CHI '12: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Pages 1095 - 1104

https://doi.org/10.1145/2207676.2208556

Published: 05 May 2012 Publication History

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.

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Index Terms

Comparing averages in time series data
1. Human-centered computing

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Published In

cover image ACM Conferences

CHI '12: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

May 2012

3276 pages

ISBN:9781450310154

DOI:10.1145/2207676

General Chair:
Joseph A. Konstan
University of Minnesota
,
Program Chairs:
Ed H. Chi
Google
,
Kristina Höök
Mobile Life at KTH

Copyright © 2012 ACM.

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Published: 05 May 2012

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Moritz DPadilla LNguyen FFranconeri S(2024)Average Estimates in Line Graphs Are Biased Toward Areas of Higher VariabilityIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.332658930:1(306-315)Online publication date: 1-Jan-2024
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