Calculating Probability of Sixth Die Face on Nth Consecutive Throw

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Discussion Overview

The discussion revolves around calculating the probability of the sixth face of a fair die appearing on the Nth consecutive throw, particularly in the context of stopping after all six faces have been rolled. Participants explore various approaches to determining this probability, including combinatorial methods and the use of functions.

Discussion Character

  • Exploratory
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant asks how to determine the probability that the sixth side of a fair die will appear on the Nth consecutive throw.
  • Another suggests a formula P(N)=1/6^N, but this is questioned by others who clarify the problem's context.
  • A participant proposes that the probability of stopping on the Nth throw, after rolling all six faces, can be expressed as P(N=6)=6!/(6^6) and P(N<6)=0, but expresses confusion about N>1.
  • One participant notes that calculating the probability involves summing many individual cases, indicating a complex solution.
  • Another introduces the concept of counting onto functions to relate the problem to combinatorial mathematics.
  • Several participants discuss a formula for counting onto functions, with one providing a specific summation formula involving binomial coefficients.
  • Another participant suggests a strategy of counting the number of ways to get at least one of each of five numbers in N-1 throws, proposing that this simplifies the problem.
  • One participant introduces a notation for the number of ways a die can land on all but one face, leading to a probability expression involving F_k(n).
  • There is mention of Stirling numbers of the second kind in relation to the counting of functions, with participants acknowledging the connection to their calculations.
  • A later post introduces a related problem about the expected number of throws to get a six, discussing the derivation of the expected value.

Areas of Agreement / Disagreement

Participants express various viewpoints and approaches, with no consensus reached on a single method for calculating the probability. Multiple competing models and interpretations of the problem remain present throughout the discussion.

Contextual Notes

Participants note the complexity of the problem and the need for careful consideration of combinatorial principles. Some assumptions about the definitions and conditions of the problem are not fully resolved, particularly regarding the calculations for N>1.

LittleWolf
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Does anyone know how to determine the probability that the sixth side of a fair die will appear on the Nth consecutive throw.
 
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I suggest you sit down and try to reason this through, but it's just

[tex]P(N)=\frac{1}{6^N}[/tex]
 
The problem I was trying to ask was " You throw a die until all six faces have shown up and then you stop." What is the probability that you stop on the Nth throw. I believe that P(N=6)=6!/(6^6) and P(N<6)=0 but I am confused about the probability of stopping for N>1.
 
I don't expect that to have a simple answer. It's easy enough to answer:

"What is the probability of getting u 1's, v 2's, w 3's, x 4's, y 5's, and z 6's in N (= u+v+w+x+y+z) throws"

But then to get the answer to your problem, you have to add up a lot of individual cases. :frown:
 
Counting the number of ways that all the faces can come up on n rolls is the same as counting the number of onto functions from {1, 2, ... n} to {1, 2, 3, 4, 5, 6}, since each time you roll the die you effectively map the number of the roll to one of the faces on the die.
 
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There is a formula for counting the number of onto functions.
 
I think a good strategy would be counting the number of ways to get at least 1 of each of 5 numbers in N-1 throws and exactly 0 of the last. This way order doesn't matter, which simplifies the problem (I think/hope). This should be exactly six times P(N).
 
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Musing aloud

Let [tex]F_k(n)[/tex] represent the number of ways a die with [tex]k[/tex] equiprobible faces can land once on all but one faces at least once, with the last face never coming up, out of [tex]n+k-1[/tex] throws. Clearly the probability of the desired event is [tex]P(n)=\frac{F_6(n-6)}{6^n}[/tex] as long as n>=6.

[tex]F_6(0)=6\cdot5![/tex], since there are 5! ways for the 5 objects to be chosen once each, and 6 ways to choose which element is last. This brings us to P(6)=6!/6^6=5/324, as LittleWolf pointed out.

In fact, in general [tex]F_k(0)=\frac{k!}{k^k}[/tex], since each of the faces other than the last must be landed on exactly once.

[tex]F_2(n)=2[/tex], since either all the results are 1 or all the results are 2.

[tex]F_3(n)=3\left(\sum_{l=1}^{n+1}{n+2\choose l}\right)=3\left(\sum_{l=0}^{n+2}{n+2\choose l}-{n+2\choose0}-{n+2\choose n+2}\right)=3\left(2^{n+1}-2\right)[/tex]

Is there some good pattern, or some Bell-related OEIS sequence I'm missing here?
 
I said there was already a formula for counting the number of onto functions. Given that LittleWolf was asked the problem, he probably already has that formula. I looked it up and this is it, using ^ for exponentiation and C(a, b) for "a choose b":

The number of onto functions from a set of size m to a set of size n is equal to the sum for i = 0 to n of ((-1)^i * C(n, i) * (n - i)^m).

So to find the answer to LittleWolf's question, you substitute N for m and 6 for n in that expression.
 
  • #10
BicycleTree said:
The number of onto functions from a set of size m to a set of size n is equal to the sum for i = 0 to n of ((-1)^i * C(n, i) * (n - i)^m).

So to find the answer to LittleWolf's question, you substitute N for m and 6 for n in that expression.

First: Thanks for the formula, I couldn't think of that one. Actually, I'm not sure if I even knew of it before... it looks vaguely familliar, but no more. If you don't mind I'll [tex]\TeX[/tex] it so I can follow it a little better...

[tex]\sum_{i=0}^{n}(-1)^i{n\choose i}(n-i)^m=\sum_{i=0}^{n-1}(-1)^i{n\choose i}(n-i)^m[/tex]

[tex]\sum_{i=0}^{6}(-1)^i{6\choose i}(6-i)^N= {6\choose 0}6^N-{6\choose 1}5^N+{6\choose 2}4^N-{6\choose 3}3^N+{6\choose 4}2^N-{6\choose 5}= 6^N-6\cdot5^N+15\cdot4^N-20\cdot3^N+15\cdot2^N-6[/tex]

OK... this is the number of ways to have all 6 faces show up by the Nth turn. The probability of it turning up on the Nth turn is then
[tex]P(N)=6^{-N}\left((6^N-6\cdot5^N+15\cdot4^N-20\cdot3^N+15\cdot2^N-6)-(6^{N-1}-6\cdot5^{N-1}+15\cdot4^{N-1}-20\cdot3^{N-1}+15\cdot2^{N-1}-6)\right)[/tex]

Right?
 
  • #11
Looks right to me.

I think the reason it might be familiar to you is that (so says my book) the summation is a Stirling number of the second kind, S(m, n), multiplied by n!.
http://mathworld.wolfram.com/StirlingNumberoftheSecondKind.html
The Stirling numbers count the number of ways to divide a set of size m into n nonempty sets, so to count functions you want to have the order of the n sets important so you multiply by n!.
 
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  • #12
BicycleTree said:
Looks right to me.

I think the reason it might be familiar to you is that (so says my book) the summation is a Stirling number of the second kind, S(m, n), multiplied by n!.

I thought that Stirling numbers (of the second kind; I've never used Stirling numbers of the first kind) should come up, but I didn't actually follow through with that.

Thanks for the formula!
 
  • #13
Modifying your notation, the probability P(N,6) is the cumulative distribution function. The probability that the last face shows up on the Nth throw is 6*P(N,5). If you consider the recursion formula for Stirling#s of the 2nd kind, you can see why P(N,6) is the CDF. Thanks to everyone for clearing up this problem.
 
  • #14
a related problem is
what is the the expected number of throws to get a six on a fair dice

this was raised at
https://www.physicsforums.com/archive/topic/t-45262_The_expected_value_of_a_Geometric_Series.html
which seems to be closed now.

yes the answer is 6 but how do you prove it.

if p=1/6 and q=1-p
x is the number of throws

then E(x) is sum(x.P(X=x)) = sum(x.p.q^(x-1))
the sums are for x=1 to infinity
i.e. E(x) is p(1 +2q +3q^2 +4q^3+...)

let S= E(x)/p = 1 +2q +3q^2 +4q^3+...

rearranging the sum as
S=
1 + q + q^2 + q^3 + ...
+ q + q^2 + q^3 + ..
+ q^2 + q^3 +...
then rearrange these lines as

S= 1 ( 1 + q + q^2 + q^3 + ...)
+q (1 + q + q^2 + q^3 + ...)
+q^2 ( 1 + q + q^2 + q^3 + ...)
...

so S= (1 + q + q^2 + q^3 + ...)*(1 + q + q^2 + q^3 + ...)

i.e S= (1 + q + q^2 + q^3 + ...)^2
this geometric series sums to 1/(1-q)

i.e. S= (1/(1-q))^2
i.e. = 1/p^2
So E(x) =pS = 1/p
in the case of six sided die, p=1/6, E(x) =6


this solutiuon found at http://math.berkeley.edu/~mchrist/Math55/Lectures/L28.pdf

probably a good source several problems in this forum
 
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