Graphing methods for Kendall's {\tau}

Understand

Ranked data is commonly used in research across many fields of study including medicine, biology, psychology, and economics.

• One common statistic used for analyzing ranked data is Kendall's {\tau} coefficient, a non-parametric measure of rank correlation which describes the strength of the association between two monotonic continuous or ordinal variables.
• While the mathematics involved in calculating Kendall's {\tau} is well-established, there are relatively few graphing methods available to visualize the results.
• Here, we describe a visualization method and provide an interactive app for graphing Kendall's {\tau} which uses a series of rigid Euclidean transformations along a Cartesian plane to map rank pairs into discrete quadrants.