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Uninterpretable graphs at a scientific conference

Zen FaulkesiD

Abstract

Comparing averages requires knowing sample variation, which can be shown visually using a bar graph with error bars or a box plot. Because error bars and box plots can show different measures, they must be labelled to be interpretable. Of graphs of averages shown at a scientific conference in 2020, 87.5% of graphs did not contain enough information on the slide to interpret them. The only graphs that were fully interpretable (12.5%) were bar graphs. By comparison, 92% of graphs of averages published in a journal in the same field contained enough information to interpret them. While conferences are not and should not be as stringent about data presentation as journals, that a statistical value as simple as an average are not clearly presented suggests graphs are created by rote.

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