Seemingly simple expected value question

I have no idea how to solve a problem which goes something like this:

"In a neighborhood, 30 people live in 30 different houses. What is the expected number of houses that one must visit in order to find 6 particular people?"

I tried several approaches which gave me strange answers, although I remember one time where I miraculously got something around 23, which seems most reasonable.

Can anyone help me?

#Combinatorics #ExpectedValue #Finn

Note by Finn Hulse
6 years, 2 months ago

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Comments

There are (306)\dbinom{30}{6} ways in which the 66 people can be "distributed" amongst the 3030 houses with regards to any sequence we choose to take, each of which is equally likely. Now it's the house that we find the 66th person in that will determine the tally of houses we've had to check. So say the last person was found in the 2424th house we've checked; there are (235)\dbinom{23}{5} ways we could then have found the other 55 people before getting to this last house. So the expected value will be

1(306)k=529(k+1)(k5)=1867=26.57\dfrac{1}{\dbinom{30}{6}} \displaystyle\sum_{k=5}^{29} (k + 1)\dbinom{k}{5} = \dfrac{186}{7} = 26.57 to 2 decimal places.

That is, for 5k29,5 \le k \le 29, if the last person found is in the (k+1)(k + 1)st house, then there were (k5)\dbinom{k}{5} ways in which we found the previous five people before getting to this last house, each of which was equally likely. The "weight" of each of these outcomes with respect to the expected value calculation is (k+1),(k + 1), resulting in the above calculation.

It's interesting to analyze the general discrete function

E(n,m)=1(nm)k=m1n1(k+1)(km1)E(n,m) = \dfrac{1}{\dbinom{n}{m}} \displaystyle\sum_{k=m-1}^{n-1} (k + 1)\dbinom{k}{m-1}

representing the expected number of houses that need to be visited to find mm people distributed amongst nn houses. For n=30n = 30 and starting at m=1m = 1 we obtain the following results:

15.5,20.67,23.25,24.8,25.83,26.57,27.13,27.56,27.9,28.18,.....15.5, 20.67, 23.25, 24.8, 25.83, 26.57, 27.13, 27.56, 27.9, 28.18, .....

To find 1515 people we would expect to have to visit just over 2929 houses.

Brian Charlesworth - 6 years, 2 months ago

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The general form is m(n+1)m+1 \dfrac{m(n+1)}{m+1}

Siddhartha Srivastava - 6 years, 2 months ago

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Great! I hadn't seen that formula before. I'll have to see now how to simplify my formula for E(n,m)E(n,m) to obtain yours.

Brian Charlesworth - 6 years, 2 months ago

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@Brian Charlesworth Don't ask me why I just saw this now, but...

Your summand is (k+1)(km1)=m(k+1m), (k+1)\binom{k}{m-1} = m\binom{k+1}{m}, and now you can factor out the mm to get E(m,n)=m(nm)k=m1n1(k+1m) E(m,n) = \frac{m}{\binom{n}{m}} \sum_{k=m-1}^{n-1} \binom{k+1}{m} and that sum, (mm)+(m+1m)++(nm) \binom{m}{m} + \binom{m+1}{m} + \cdots + \binom{n}{m} , is well-known to equal (n+1m+1) \binom{n+1}{m+1} .

So E(m,n)=m(n+1m+1)(nm)=m(n+1)m+1 E(m,n) = \frac{m \binom{n+1}{m+1}}{\binom{n}{m}} = \frac{m(n+1)}{m+1} as desired.

Patrick Corn - 5 years, 4 months ago

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@Patrick Corn Great! Once you rewrite the summand that way the "hockey-stick" identity does conveniently pop out. Thanks for proving that simplification. :)

Brian Charlesworth - 5 years, 4 months ago

Thanks man! :D

Finn Hulse - 6 years, 2 months ago

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You're welcome. :) The value of 26.5726.57 was higher than I would have anticipated, but "intuition" is pretty unreliable when it come to probability and expected value questions.

Brian Charlesworth - 6 years, 2 months ago

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@Brian Charlesworth A possible (but ultimately wrong) intuition is that "if everyone is equally distributed, then I would expect the 6th person to appear in the last 16 \frac{1}{6} of the houses, so the answer is about 27."

Calvin Lin Staff - 6 years, 2 months ago

Your question is analogous to this one

Siddhartha Srivastava - 6 years, 2 months ago

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Hmm.

Finn Hulse - 6 years, 2 months ago
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