A series of artificial populations with different types of spatial distribution is used to test the value of a number of published indices in identifying non-randomness. Among tests based on distance measurements, that of Hopkins is generally the most powerful, through there are reasons for preferring that of Pielou where the vegetation has not been completely mapped. Among tests involving quadrat measurements, the variance/mean ratio appears to be best. Where contiguous series of quadrats are available hierarchical analysis of variance is a more powerful test than Monte-Carlo pairing of quadrats, though the latter is a more flexible technique.