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Original Articles

A Table for Estimating the Mean of a Lognormal Distribution

Pages 632-636 | Published online: 10 Apr 2012
 

Abstract

If experimental data have been analyzed using a logarithmic transformation of the actual observations, taking the antilog of the mean of the transformed variables yields a biased estimate of the mean μ of the original variable. To obtain an unbiased estimate of this mean a correction for bias must be applied. The table at the end of this note provides values of a function of the sample size and variance of data transformed to logarithms to base 10 which, when added to the mean of the transformed data, yields an unbiased estimate of the mean of the original variable after transforming back. This estimate is more efficient than the mean of the untransformed observations.

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