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This post is a rundown of a workflow that I use for preparing group-comparison graphs that are ready to include in nearly any kind of report. This post is sectioned out piece-by-piece to better demonstrate the impacts of each function and argument for ggplot, and also incorporates statistical hypothesis tests.

Building off of raincloud and fadecloud plots, I introduce two new styles for plotting data transparently: (1) the faded dotplot and (2) the shadeplot. Both leverage the r package ggdist to present stacked raw data, overall distribution, and summary stats while minimizing visual clutter.