On the Random Sampling of Pairs, with Pedestrian examples

Abstract

Suppose one desires to randomly sample a pair of objects such as socks, hoping to get a matching pair. Even in the simplest situation for sampling, which is sampling with replacement, the innocent phrase "the distribution of the color of a matching pair" is ambiguous. One interpretation is that we condition on the event of getting a match between two random socks; this corresponds to sampling two at a time, over and over without memory, until a matching pair is found. A second interpretation is to sample sequentially, one at a time, with memory, until the same color has been seen twice. We study the difference between these two methods. The input is a discrete probability distribution on colors, describing what happens when one sock is sampled. There are two derived distributions --- the pair-color distributions under the two methods of getting a match. The output, a number we call the discrepancy of the input distribution, is the total variation distance between the two derived distributions. It is easy to determine when the two pair-color distributions come out equal, that is, to determine which distributions have discrepancy zero, but hard to determine the largest possible discrepancy. We find the exact extreme for the case of two colors, by analyzing the roots of a fifth degree polynomial in one variable. We find the exact extreme for the case of three colors, by analyzing the 49 roots of a variety spanned by two seventh-degree polynomials in two variables. We give a plausible conjecture for the general situation of a finite number of colors, and give an exact computation of a constant which is a plausible candidate for the supremum of the discrepancy over all discrete probability distributions. We briefly consider the more difficult case where the objects to be matched into pairs are of two different kinds, such as male-female or left-right.