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arXiv · 1208.1932

Statistical Distortion: Consequences of Data Cleaning

Tamraparni Dasu·Ji Meng Loh
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Abstract

We introduce the notion of statistical distortion as an essential metric for measuring the effectiveness of data cleaning strategies. We use this metric to propose a widely applicable yet scalable experimental framework for evaluating data cleaning strategies along three dimensions: glitch improvement, statistical distortion and cost-related criteria. Existing metrics focus on glitch improvement and cost, but not on the statistical impact of data cleaning strategies. We illustrate our framework on real world data, with a comprehensive suite of experiments and analyses.

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Tamraparni Dasu, Ji Meng Loh. 2012-08-09. Statistical Distortion: Consequences of Data Cleaning. https://arxiv.org/abs/1208.1932

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