  Maher also objects that the attribute itself, such as “blue”, might be a priori relevant to its proportion in the sample and hence to matching. For example, if “blue” is one of a large range of possible colors, then a priori it is unlikely that an individual is blue and unlikely that a sample will have many blue items. As with any Bayesian reasoning, a prior probability close to zero (or one) requires a lot of evidence to overcome; in this case, we would conclude that a sample with a high proportion of blue items was most likely a coincidence, and the posterior probability of the sample matching the population would still not be high.