Abstract
In this paper, we discuss benchmark data sets proposed by Anscombe and Longley for measuring the numerical accuracy of statistical algorithms. We show that these benchmarks present an unduly optimistic assessment of numerical accuracy. We demonstrate that the cause of this unwarranted optimism is the use of integer values in the benchmarks. Alternative benchmarks are proposed which avoid the problems brought about by the integer values and provide a more realistic assessment of numerical accuracy under varying data conditions.
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