Estimates of genetic diversity in major geographic regions are frequently made by pooling all individuals into regional aggregates. This method can potentially bias results if there are differences in population substructure within regions, since increased variation among local populations could inflate regional diversity. A preferred method of estimating regional diversity is to compute the mean diversity within local populations. Both methods are applied to a global sample of craniometric data consisting of 57 measurements taken on 1734 crania from 18 local populations in six geographic regions: sub-Saharan Africa, Europe, East Asia, Australasia, Polynesia, and the Americas. Each region is represented by three local populations. Both methods for estimating regional diversity show sub-Saharan Africa to have the highest levels of phenotypic variation, consistent with many genetic studies. Polynesia and the Americas both show high levels of regional diversity when regional aggregates are used, but the lowest mean local population diversity. Regional estimates of FST made using quantitative genetic methods show that both Polynesia and the Americas also have the highest levels of differentiation among local populations, which inflates regional diversity. Regional differences in FST are directly related to the geographic dispersion of samples within each region; higher FST values occur when the local populations are geographically dispersed. These results show that geographic sampling can affect results, and suggest caution in making inferences regarding regional diversity when population substructure is ignored.