Studies on the precision of chemical methods of analysis, and the associated 'sampling uncertainty', suggest that analysis of eight replicate sample units (the sample size) is required to ensure adequate analytical precision. The primary purpose of this work was to assess whether these findings are equally applicable in microbiological examination of foods. We examined the effect of sample size on the analytical precision of microbiological data by iteratively 're-sampling without replacement' (SNR). Using both theoretical data sets and colony counts from foods we demonstrate that SNR provides an effective and efficient guide to (a) choosing the number of samples to be examined in order to optimise precision and (b) deciding whether logarithmic transformation of the raw data is appropriate. We also discuss theoretical aspects of the procedure and their impact on the results obtained.