Math Matters in Communication: Manipulation and Misrepresentation in Data Displays

Abstract

Whether you walk in industry or academia (or both), the ability to interrogate data and the way it is displayed visually matters. We discuss how misleading graphics and data displays are constructed, focusing on five means of manipulating data: 1) scale, 2) sample size, 3) confounding variables, 4) data outliers, and 5) the visual selected for the story. We focus on these areas as some of the most common sources of concern in misleading or inaccurate data displays, yet the mathematics underlying these concepts is often absent from or covered only superficially in professional communication instruction. We further offer examples to both mathematics and communication instructors for helping students recognize misleading graphics and how to avoid them, encouraging interdisciplinary bridges to meet the multidisciplinary requirements of creating ethical data displays.