Simulations Of Error Propagation For Prioritizing Data Accuracy Improvement Efforts

نویسنده

  • Irit Askira Gelman
چکیده

Models of the association between input accuracy and output accuracy imply that, for any given application, the effect of input errors on the output error rate generally varies in size depending on the choice of the specific input. While errors in one input may have a dramatic effect on the output error rate, a comparable or even higher error rate in another input may have a negligible effect. Clarification of this variation can be useful in data-quality management settings, since it can guide resource allocation decisions. Inputs in which errors exhibit a higher negative effect on the output would naturally earn higher priority. The assistance that the models provide in the detection of such variation is, however, insufficient. Mainly, applying such a model can be painstaking. Therefore, there is a need to construct theories that illustrate the effects of errors in relatively broad scenarios. This study aims at such an introductory theory. The study applies simulations in order to illustrate error propagation in two basic information processing operations: the Boolean binary logical OR and logical AND. These operations are commonly used in the course of decision-making tasks. The results imply two simple rules for guiding data-management resource-allocation decisions. The findings also challenge common beliefs: they point to conditions in which a higher input accuracy generates lower output accuracy.

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تاریخ انتشار 2007