Data visualizations and graphs are increasingly common in both scientific and mass media settings. While graphs are useful tools for communicating patterns in data, they also have the potential to mislead viewers. In five studies, we provide empirical evidence that y-axis truncation leads viewers to perceive illustrated differences as larger (i.e., a truncation effect). This effect persisted after viewers were taught about the effects of y-axis truncation and was robust across participants, with 83.5% of participants across all 5 studies showing a truncation effect. We also found that individual differences in graph literacy failed to predict the size of individuals' truncation effects. PhD students in both quantitative fields and the humanities were susceptible to the truncation effect, but quantitative PhD students were slightly more resistant when no warning about truncated axes was provided. We discuss the implications of these results for the underlying mechanisms and make practical recommendations for training critical consumers and creators of graphs.
Data visualizations and graphs are increasingly common in both scientific and mass media settings. How might graphs mislead? In the present work, we provide empirical evidence across five studies for a clear, persistent means of misleading readers: the truncation effect for bar graphs. This effect occurs when a bar graph with a truncated axis exaggerates the perceived size of an illustrated difference. In the first study, we present participants with bar graphs on a variety of topics and manipulate y-axis truncation within-subjects. We find evidence for a consistent effect of truncation. In four subsequent studies, we explore whether this effect is modified by a warning about the nature of the manipulation, a 24-hour delay, and in a specialized participant population (PhD students in the humanities and quantitative fields). This truncation effect persists in each of these contexts, but is attenuated after warnings and in specialized participant populations.
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