Significant diversity between occupants and their presence and actions results in major uncertainty with regard to predicting building performance. However, many current occupant modelling approaches – even stochastic ones – suppress occupant diversity by focusing on developing representative occupants. Accordingly, existing approaches tend to limit the ability of stochastic occupant models to provide probabilistic building performance distributions. Using occupancy data from 16 private offices, this paper evaluated three hypotheses: (1) occupant parameters have a continuous distribution rather than discrete; (2) modelling occupants from aggregated data suppresses diversity; and (3) randomly selecting occupant traits exaggerates synthetic population diversity. The paper indicates that samples sizes for the studied occupants would have more appropriately been an order of magnitude higher: hundreds. This introductory paper shows that there are many future research needs with regard to modelling occupants.