Published In

Stats

Document Type

Article

Publication Date

9-27-2024

Abstract

The histogram remains a widely used tool for visualization of the distribution of a continuous variable, despite the disruption of binning the underlying continuity into somewhat arbitrarily sized discrete intervals imposed by the simplicity of its pre-computer origins. Alternatives include three visualizations, namely a smoothed density distribution such as a violin plot, a box plot, and the direct visualization of the individual data values as a one-dimensional scatter plot. To promote ease of use, the plotting function discussed in this work, Plot(x), automatically integrates these three visualizations of a continuous variable x into what is called a VBS plot here, tuning the resulting plot to the sample size and discreteness of the data. This integration complements the information derived from the histogram well and more easily generalizes to a multi-panel presentation at each level of a second categorical variable.

Rights

Copyright: © 2024 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

DOI

10.3390/stats7030058

Persistent Identifier

https://archives.pdx.edu/ds/psu/42580

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