Truncating the Y-Axis: Threat or Menace?

要旨

Bar charts with y-axes that don't begin at zero can visually exaggerate effect sizes. However, advice for whether or not to truncate the y-axis can be equivocal for other visualization types. In this paper we present examples of visualizations where this y-axis truncation can be beneficial as well as harmful, depending on the communicative and analytic intent. We also present the results of a series of crowd-sourced experiments in which we examine how y-axis truncation impacts subjective effect size across visualization types, and we explore alternative designs that more directly alert viewers to this truncation. We find that the subjective impact of axis truncation is persistent across visualizations designs, even for designs with explicit visual cues that indicate truncation has taken place. We suggest that designers consider the scale of the meaningful effect sizes and variation they intend to communicate, regardless of the visual encoding.

受賞
Honorable Mention
キーワード
Information visualization
Deceptive Visualization
著者
Michael Correll
Tableau Research, Seattle, WA, USA
Enrico Bertini
New York University, New York, NY, USA
Steven Franconeri
Northwestern University, Evanston, IL, USA
DOI

10.1145/3313831.3376222

論文URL

https://doi.org/10.1145/3313831.3376222

会議: CHI 2020

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2020.acm.org/)

セッション: Perception of visualizations

Paper session
316A MAUI
5 件の発表
2020-04-29 18:00:00
2020-04-29 19:15:00
日本語まとめ
読み込み中…