Abstract
Why do some ideas endure, while others end up nearly forgotten? Why do some models resonate and intuitively explain, while others leave us perplexed and puzzled? In the history of statistics, entities such as the Gauss distribution—also known as the ‘normal’ distribution—have been introduced and discussed in technical and mathematical ways, but also used to describe general connections and patterns related to demography, criminology, medicine, and more. When Carl Friedrich Gauss introduced his famous distribution in the beginning of the 19th century, it was used to measure the precision of astronomical observations. However, the intuitive elegance of the bell-shaped curve soon found its way into other disciplines, marking not only a central development in statistics, but also an entirely new way of seeing and thinking about the world through data: a world where measurements of different sorts and from a variety of contexts cluster tightly around a mean, with a rapidly decaying minority of outliers extending along the tails. Yet, what kind of formation of knowledge does a bell curve represent, and why did it seem to offer such a persuasive description of contexts as different as, e.g., average human height, poverty records, or inherited physical and psychological attributes? This paper engages with the aesthetic dimensions of data-driven knowledge production. Using the idea of the ‘normal’ distribution as starting point, it asks how knowledge is produced based on data, and how it manifests itself as knowledge through the means of persuasive diagrams.
Presenters
Maja Bak HerriePostdoc, Department of Art History, Aesthetics & Culture and Museology, Aarhus University, Denmark
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
KEYWORDS
DATA-DRIVEN THINKING, AESTHETICS, DIAGRAM, DIAGRAMMATICS
