Infovis and Statistical Graphics: Different Goals, Different Looks
Infovis and Statistical Graphics: Different Goals, Different Looks
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Infovis 和统计图形：不同的目标，不同的外观
DOI：
10.1080/10618600.2012.761137
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发表时间：
2013
影响因子：
2.4
通讯作者：
Antony Unwin
中科院分区：
文献类型：
--
作者：
Andrew Gelman;Antony Unwin
在过去的一个世纪里，统计文献零星地认识到图形显示在统计实践中的重要性，在随后的几十年里，随着Tukey的探索性数据分析和Tufte的书籍，人们更广泛地认识到这一点。但是统计图形仍然占据着一个尴尬的中间位置：在统计学中，探索性和图形化方法代表了一个小的子领域，并且没有很好地与更大的建模和推理主题集成。在统计学之外，信息图表（也称为信息可视化或Infovis）的应用非常广泛，但它们的提供者和爱好者似乎对统计原理不感兴趣。我们在这里提出了一组主要从统计角度讨论的图形显示目标，并讨论了这些目标中的一些内在矛盾，这些矛盾可能会阻碍统计和Infovis领域之间的交流。我们对infois实践者和统计学家的一个建设性建议是，尽量不要把可以用两个或更多个图表更好地显示的东西塞进一个图表中。我们认识到，我们只提供一种观点，并希望本文成为图形设计师、统计学家和统计方法用户之间广泛讨论的起点。本文的目的不是批评，而是探讨不同领域的研究人员重视数据可视化不同方面的不同目标。
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.