It is common practice when calculating dose to exposed populations to average the variables that go into the dose calculation (e.g. environmental concentrations, air kerma, consumption rates, occupancy rates). This approach is simple and can be useful where data are obtained over different periods (weekly, monthly, quarterly), where samples may be bulked for some analyses but not others and where gaps in the data are present. However, such an approach does not yield information on the degree of uncertainty around the average dose calculated. An alternative approach is to estimate the dose to each individual and to obtain an average from this data set, which can then also be used to derive a measure of uncertainty around the central dose estimate. In this study, we demonstrate the variability in dose estimates using a hypothetical data set and consider the implications for sample size to achieve fixed confidence or resolving power. We recommend calculating the dose to every individual sampled, in order both to obtain the average dose and to estimate its variability. We argue that it is best practice to obtain information as complete as possible from the available sample of individuals.