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Visualizing uncertainty in areal data with bivariate choropleth maps, map pixelation and glyph rotation
Author(s) -
Lucchesi Lydia R.,
Wikle Christopher K.
Publication year - 2017
Publication title -
stat
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.61
H-Index - 18
ISSN - 2049-1573
DOI - 10.1002/sta4.150
Subject(s) - bivariate analysis , bivariate data , computer science , centroid , univariate , geocoding , statistics , glyph (data visualization) , spatial analysis , zoom , data mining , visualization , cartography , geography , multivariate statistics , mathematics , artificial intelligence , geology , petroleum engineering , lens (geology)
In statistics, we quantify uncertainty to help determine the accuracy of estimates, yet this crucial piece of information is rarely included on maps visualizing areal data estimates. We develop and present three approaches to include uncertainty on maps: (1) the bivariate choropleth map repurposed to visualize uncertainty; (2) the pixelation of counties to include values within an estimate's margin of error; and (3) the rotation of a glyph, located at a county's centroid, to represent an estimate's uncertainty. The second method is presented as both a static map and visuanimation. We use American Community Survey estimates and their corresponding margins of error to demonstrate the methods and highlight the importance of visualizing uncertainty in areal data. An extensive online supplement provides the R code necessary to produce the maps presented in this article as well as alternative versions of them. Copyright © 2017 John Wiley & Sons, Ltd.