An Improved Boxplot for Univariate Data

ABSTRACT

The boxplot is an effective data-visualization tool useful in diverse applications and disciplines. Although more sophisticated graphical methods exist, the boxplot remains relevant due to its simplicity, interpretability, and usefulness, even in the age of big data. This article highlights the origins and developments of the boxplot that is now widely viewed as an industry standard as well as its inherent limitations when dealing with data from skewed distributions, particularly when detecting outliers. The proposed Ratio-Skewed boxplot is shown to be practical and suitable for outlier labeling across several parametric distributions.

KEYWORDS:

• Asymmetric distribution
• Bowley's coefficient
• Fence constant
• Outliers
• Skewness

Acknowledgments

The authors are grateful for the interest and the detailed comments of the editor, the associate editor, and two anonymous referees that contributed to an improved presentation. Assistance from the editorial office is also acknowledged.