Infovis and Statistical Graphics: Different Goals, Different Looks
Инфовиз и статистическая графика: разные цели, разный облик
2013-01-01
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exploratory data analysisgraphical displaysinformation visualizationstatistical graphicsvisualization goals
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Abstract (AI)
The importance of graphical displays in statistical practice has been recognized sporadically in the statistical literature over the past century, with wider awareness following Tukey's Exploratory Data Analysis and Tufte's books in the succeeding decades. But statistical graphics still occupy an awkward in-between position: within statistics, exploratory and graphical methods represent a minor subfield and are not well integrated with larger themes of modeling and inference. Outside of statistics, infographics (also called information visualization or Infovis) are huge, but their purveyors and enthusiasts appear largely to be uninterested in statistical principles.We present here a set of goals for graphical displays discussed primarily from the statistical point of view and discuss some inherent contradictions in these goals that may be impeding communication between the fields of statistics and Infovis. One of our constructive suggestions, to Infovis practitioners and statisticians alike, is to try not to cram into a single graph what can be better displayed in two or more. We recognize that we offer only one perspective and intend this article to be a starting point for a wide-ranging discussion among graphic designers, statisticians, and users of statistical methods. The purpose of this article is not to criticize but to explore the different goals that lead researchers in different fields to value different aspects of data visualization.
Key Findings
1
A suggested constructive practice is to avoid cramming multiple messages into a single graph; use two or more displays when clearer.
2
Infovis practitioners often ignore core statistical principles, creating a gap between Infovis and statistical practice.
3
Statistical graphics and information visualization (Infovis) have different goals and therefore different design aesthetics and priorities.
4
There are inherent contradictions among graphical goals that impede communication between statistics and Infovis communities.
5
Within statistics, exploratory and graphical methods remain a minor, poorly integrated subfield relative to modeling and inference.
Research Object
Graphical displays for data (statistical graphics and information visualization/Infovis)
Research Subject
Different goals, priorities, and design trade-offs that lead statisticians and Infovis practitioners to value different aspects of data visualization and the resulting communication/interpretation implications
Publication Details
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2013-01-01
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