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Graphical Tests for Power Comparison of Competing Designs

机译:竞争设计的图形比较的图形测试

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Lineups [4, 28] have been established as tools for visual testing similar to standard statistical inference tests, allowing us to evaluate the validity of graphical findings in an objective manner. In simulation studies [12] lineups have been shown as being efficient: the power of visual tests is comparable to classical tests while being much less stringent in terms of distributional assumptions made. This makes lineups versatile, yet powerful, tools in situations where conditions for regular statistical tests are not or cannot be met. In this paper we introduce lineups as a tool for evaluating the power of competing graphical designs. We highlight some of the theoretical properties and then show results from two studies evaluating competing designs: both studies are designed to go to the limits of our perceptual abilities to highlight differences between designs. We use both accuracy and speed of evaluation as measures of a successful design. The first study compares the choice of coordinate system: polar versus cartesian coordinates. The results show strong support in favor of cartesian coordinates in finding fast and accurate answers to spotting patterns. The second study is aimed at finding shift differences between distributions. Both studies are motivated by data problems that we have recently encountered, and explore using simulated data to evaluate the plot designs under controlled conditions. Amazon Mechanical Turk (MTurk) is used to conduct the studies. The lineups provide an effective mechanism for objectively evaluating plot designs.
机译:阵容[4,28]已被建立为类似于标准统计推断测试的视觉测试工具,使我们能够客观地评估图形结果的有效性。在仿真研究中[12],阵容被证明是有效的:视觉测试的功能可与经典测试相提并论,而在分配假设方面则不那么严格。这使得在无法或不能满足常规统计测试条件的情况下,阵容强大而功能强大的工具。在本文中,我们介绍了阵容作为评估竞争性图形设计能力的工具。我们重点介绍一些理论属性,然后显示两项评估竞争性设计的研究的结果:两项研究均旨在达到我们感知能力的极限,以突出设计之间的差异。我们将评估的准确性和速度作为成功设计的标准。第一项研究比较了坐标系的选择:极坐标系和直角坐标系。结果显示了对笛卡尔坐标的有力支持,可以快速找到准确的斑点图案答案。第二项研究旨在发现分布之间的转移差异。两项研究均受我们最近遇到的数据问题的启发,并探索使用模拟数据在受控条件下评估样地设计。使用Amazon Mechanical Turk(MTurk)进行研究。阵容为客观评估样地设计提供了一种有效的机制。

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