A container holds N coupons. You draw successive coupons from the container, observe the coupon drawn, and then replace the coupon. What is the expected number of draws needed until all N coupons have been seen at least once?
Challenge: what is the probability that the process ends after exactly M draws?
Solution
Answer: N + N/2 + N/3 + \cdots + N/(N-1) + 1
Proof:
Fix N, and let f(m) be the expected number of draws until we see all coupons, provided that we have seen m coupons so far. The number that we are looking for is f(0), and we know that f(N) = 0.
Observe that when we draw a random coupon, we have a m/N chance of drawing a coupon we have seen, and thus wasting our draw. After that draw, the expected number of draws is still f(m). But we also have a 1-m/N chance of drawing a new coupon, after which our expected number becomes f(m+1).
So f(m) = \frac{m}{N}(1 + f(m)) + (1-\frac{m}{N})(1 + f(m+1))
which is equivalent to f(m) = f(m+1) + \frac{N}{N-m}
Since f(N) = 0, one can inductively prove that f(m) = \frac{N}{1} + \frac{N}{2} + \cdots + \frac{N}{N-m}
Solution to challenge problem
In order for the M-th draw to be the last draw, it must be the first occurrence of the last coupon needed. Let's say the last draw is N, then the first M-1 draws must be formed solely by coupons 1, \cdots, N-1 where each coupon appears at least once.
Let a_r be the number of strings with length r where each letter can be one of 1, \cdots, N-1. Then the probability in question is Na_{M-1}/ N^M
Also, we have the following relationship (think Exponential Generating Function):
\sum_{r=0}^{\infty} \frac{a_r}{r!}x^r = ( \sum_{r=1}^{\infty} \frac{1}{r!}x^r ) ^{N-1}
so
RHS = (e^x - 1)^{N-1} = \sum_{k=0}^{N-1} \binom{N-1}{k} e^{kx} (-1)^{n-k-1}
Now, the coefficient of x^r in the binomial expansion is
\sum_{k=0}^{N-1} \binom{N-1}{k}\frac{k^r}{r!} (-1)^{n-k-1}
so that
a_r = \sum_{k=0}^{N-1}\binom{N-1}{k} k^r (-1)^{n-k-1}
There is (as far as I know) no known simplification for the above form.
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