Sock Drawer

July 21, 2015 in Mathematics

A drawer has 18 black socks and 14 white socks. On average, how many socks should one draw to get two equal socks? And to get two different socks?

Solution A

The answer to the first one is trivial: 3. For the second question, let $N = 18$ be the number of black socks and $M = 14$ the number of white socks. Then:

outcome probability
$bw$ $\frac{N}{N+M} \frac{M-1}{N+M+1}$
$wb$ $\frac{M}{N+M} \frac{N-1}{N+M+1}$
$bbw$ $\frac{N}{N+M} \frac{N-1}{N+M-1} \frac{M-1}{N+M}$
$wwb$ $\frac{M}{N+M} \frac{M-1}{N+M-1} \frac{N-1}{N+M}$
$bbbw$ $\frac{N}{N+M} \frac{N-1}{N+M-1} \frac{N-2}{N+M-2} \frac{M-1}{N+M-1}$
$wwwb$ $\frac{M}{N+M} \frac{M-1}{N+M-1} \frac{M-2}{N+M-2} \frac{N-1}{N+M-1}$
… …

Due to linearity of expectation, the expected value is, by definition:

Which, for the given values of $N$ and $M$, gives a result of $^{279}/_{95}$, or 2.93684.

Solution B

The definition of an negative hypergeometric distribution is:

(…) the probability of the number of elements taken without replacement from a finite population whose elements can be classified into two mutually exclusive categories like Pass/Fail, Male/Female or Employed/Unemployed that stops when a fixed number of elements of certain class have been taken

If there are $N = 18 + 14 = 32$ elements, of which $K = 18$ are defined as “successes” and the rest are “failures”, and the elements are drawn one after the other, without replacements, until $R = 1$ failures are encountered, we know that the expected value is given by:

Consider two cases: one in which the first ball drawn is black and the other in which the first ball is white . You can then calculate your average for each case and weight them as follows:

The last term refers to the first draw (which is considered separately) and the last “failure” draw, which is not counted by the negative hypergeometric distribution.

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I am a Software Engineer and aspiring Computer Science theorist. My ultimate goal is to develop AI algorithms with some provable guarantees.

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