Artigo Acesso aberto Revisado por pares

Teru Teru Bōzu : Defensive Raincloud Plots

2023; Wiley; Volume: 42; Issue: 3 Linguagem: Inglês

10.1111/cgf.14826

ISSN

1467-8659

Autores

Michael Correll,

Tópico(s)

Forest ecology and management

Resumo

Univariate visualizations like histograms, rug plots, or box plots provide concise visual summaries of distributions. However, each individual visualization may fail to robustly distinguish important features of a distribution, or provide sufficient information for all of the relevant tasks involved in summarizing univariate data. One solution is to juxtapose or superimpose multiple univariate visualizations in the same chart, as in Allen et al.'s "raincloud plots." In this paper I examine the design space of raincloud plots, and, through a series of simulation studies, explore designs where the component visualizations mutually "defend" against situations where important distribution features are missed or trivial features are given undue prominence. I suggest a class of "defensive" raincloud plot designs that provide good mutual coverage for surfacing distributional features of interest.

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