33 research outputs found
Truncating the Y-Axis: Threat or Menace?
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
How to Lie with Statistic
Darrell Huff runs the gamut of every popularly used type of statistic, probes such things as the sample study, the tabulation method, the interview technique, or the way the results are derived from the figures, and points up the countless number of dodges which are used to full rather than to inform.144p.;14x21c