This article explores how aggregate level data may be used to make inferences about individual level behaviour. A common strategy in the past was to assume that the relations evident in aggregated data are also present in individual data. Analysis of datasets where there is both individual and aggregated information demonstrates that this assumption is most often incorrect. This means that the relationships observed between variables at an aggregated level are unlikely to be observed in individual level data. This is a problem because quite often social scientists only have aggregated data for exploring individual level behaviour. A key question explored in this article is how is it possible to validly and reliably use aggregated datasets to make inferences about relationships between variables at the individual level. An example analysis is given using electoral data from the Czech Republic.