The Box Plot: A Simple Visual Method to Interpret Data

TLDR

Exploratory data analysis uses statistical techniques to uncover hidden patterns, and the box plot visually summarizes data distributions with median, quartiles, extremes, and outlier detection, aiding interpretation of complex tables. The authors aim to show how readers can use box plots to improve interpretation of complex tables. They applied box plots to tabular data from two recent articles to demonstrate this. They recommend that the box plot be used more frequently.

Abstract

Exploratory data analysis involves the use of statistical techniques to identify patterns that may be hidden in a group of numbers. One of these techniques is the "box plot," which is used to visually summarize and compare groups of data. The box plot uses the median, the approximate quartiles, and the lowest and highest data points to convey the level, spread, and symmetry of a distribution of data values. It can also be easily refined to identify outlier data values and can be easily constructed by hand. We apply box plots to tabular data from two recently published articles to show how readers can use box plots to improve the interpretation of data in complex tables. The box plot, like other visual methods, is more than a substitute for a table: It is a tool that can improve our reasoning about quantitative information. We recommend that the box plot be used more frequently.