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Firework Plot as a Graphical Exploratory Data Analysis Tool for Evaluating the Impact of Outliers in Data Exploration and Regression

机译:Firework Plot作为图形探索性数据分析工具,用于评估异常值在数据探索和回归中的影响

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摘要

Outliers can distort many measures for data analysis. We propose a new set of graphical summaries, called firework plots, as simple tools for evaluating the impact of outliers in data exploration and regression assessment. One variation of the plot focuses on the impact of extreme observations on the mean and standard deviation by using curves that trace the relative contribution to the overall summary as weights for individual observations are changed from 1 to 0 in a univariate data set. Similarly, other variations for bivariate data allow examination of the impact of changing weights on combinations of the correlation coefficient and mean with two- or three-dimensional firework plots. One variation of the plot focuses on the impact on the estimated intercept, the estimated slope, and the estimated standard deviation by using curves based on the relative contribution to the overall summary as weights for individual observations are changed from 1 to 0 in a simple linear regression analysis. Similarly, other variations for a multiple regression allow the practitioner to examine the impact of changing weights on combinations of the estimated regression coefficients and the standard error with the pairwise firework plot matrix.
机译:离群值可能会扭曲许多数据分析指标。我们提出了一套称为烟火图的图形化摘要,作为评估异常值在数据探索和回归评估中的影响的简单工具。该图的一种变化着眼于极端观测对平均值和标准差的影响,方法是使用曲线来追踪对整体汇总的相对贡献,因为在单变量数据集中各个观测的权重从1变为0。类似地,双变量数据的其他变体允许检查权重变化对相关系数和均值的影响,包括二维或三维烟花图。该图的一种变化着眼于对估计的截距,估计的斜率和估计的标准偏差的影响,方法是使用基于对总体摘要的相对贡献的曲线,因为单个观察的权重从1变为线性回归分析。类似地,多元回归的其他变体使从业者可以使用成对的烟花图矩阵来检查权重变化对估计的回归系数和标准误差的组合的影响。

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