Educational Measurement: Issues and Practice ( IF 2.7 ) Pub Date : 2020-06-08 , DOI: 10.1111/emip.12339 Zhongmin Cui
Violin plots are less known than box plots, although they are cousins in that they show similar information. In addition to median and interquartile range, a violin plot shows the distribution of the data with a rotated smoothing curve. The distribution reveals additional details on the data (e.g., the number and location of peaks). A violin plot can be either elegant like a real violin or rough like the nose of a sawfish––it depends on the shape of the data and the smoothing function. Used properly, violin plots are appealing and insightful.
This issue's cover features The Musical Relative of the Boxplot– The Violin Plot by Aron Fink from Goethe‐University Frankfurt am Main in Germany. “The graphic shows a violin plot of the bias of the ability estimates for high ability students resulting from a computerized adaptive test using four different algorithms,” Fink described. “The middle part of each violin shows a classical box‐whisker‐plot,” the German researcher continued. “The shape of the violin displays the distribution of the data.”
Fink created the graphic using the ggplot2 package in R. This package can be used to create many elegant data visualizations, violin plots included. Interested readers may refer to https://cran.r-project.org/web/packages/ggplot2/index.html for details about the ggplot2 package.
To sum up, violin plots provide an advanced visualization of the distributions in a compact and attractive format that has several advantages over common approaches like classical box or density plots. They provide practitioners and educational researchers with a novel graphical tool which can easily be created using standard software like ggplot2.
If you are interested in learning more about this informative data visualization, please contact Aron Fink (a.fink@psych.uni‐frankfurt.de). If you have any questions or suggestions on the cover in general, please email Zhongmin Cui (zhongmin.cui@act.org).
中文翻译：
封面：小提琴图
尽管小提琴图是堂兄，因为它们显示相似的信息，所以它比盒图更鲜为人知。除中位数和四分位数范围外，小提琴图还显示了具有旋转平滑曲线的数据分布。该分布揭示了有关数据的其他详细信息（例如，峰的数量和位置）。小提琴图可以像真正的小提琴一样优美，也可以像锯鱼的鼻子一样粗糙-这取决于数据的形状和平滑功能。如果正确使用，小提琴图将具有吸引力和洞察力。
本期杂志的封面介绍了德国法兰克福歌德大学的阿隆·芬克（Aron Fink）制作的“箱线图的音乐亲戚–小提琴图”。“该图显示了使用四种不同算法的计算机化自适应测试所产生的高能力学生的能力估计偏差的小提琴图，” Fink说道。这位德国研究人员继续说道：“每把小提琴的中间都有一个经典的箱须图。” “小提琴的形状显示了数据的分布。”
Fink使用R中的ggplot2软件包创建了图形。该软件包可用于创建许多精美的数据可视化效果，包括小提琴图。有兴趣的读者可以参考https://cran.r-project.org/web/packages/ggplot2/index.html以获得有关ggplot2软件包的详细信息。
综上所述，小提琴图以紧凑而诱人的格式提供了分布的高级可视化效果，与传统方法（如经典箱形图或密度图）相比，具有多个优势。它们为从业人员和教育研究人员提供了一种新颖的图形工具，可以使用诸如ggplot2的标准软件轻松创建该工具。
如果您有兴趣了解有关此信息性数据可视化的更多信息，请联系Aron Fink（a.fink@psych.uni-frankfurt.de）。如果您对封面有任何疑问或建议，请发送电子邮件至Zhongmin Cui（zhongmin.cui@act.org）。
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