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Topic: Prob of flipping coin n times, at no time with #h > #t?
Replies: 10   Last Post: Feb 14, 2013 2:25 AM

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RGVickson@shaw.ca

Posts: 1,657
Registered: 12/1/07
Re: Prob of flipping coin n times, at no time with #h > #t?
Posted: Feb 6, 2013 1:53 PM
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On Wednesday, February 6, 2013 9:12:51 AM UTC-8, Ray Vickson wrote:
> On Wednesday, February 6, 2013 5:42:18 AM UTC-8, JohnF wrote:
>

> > What's P_n, the prob of flipping a coin n times,
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> >
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> > and at no time ever having more heads than tails?
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> >
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> > There are 2^n possible h-t-... sequences of n flips,
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> >
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> > comprising a binomial tree (or pascal's triangle),
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> >
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> > with 50-50 prob of going left/right at each node.
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> >
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> > So, equivalently, how many of those 2^n paths never
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> >
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> > cross the "center line" (#h = #t okay after even number
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> >
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> > of flips)?
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> >
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> > Actual problem's a bit more complicated. For m<=n,
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> >
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> > what's P_n,m, the prob that #h - #t <= m at all times?
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> >
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> > That is, P_n above is P_n,0 here. Equivalently, how
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> >
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> > many of those binomial tree paths never get >m past
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> >
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> > the "center line"?
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> >
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> > --
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> >
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> > John Forkosh ( mailto: j@f.com where j=john and f=forkosh )
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>
>
> Feller, "Introduction to Probability Theory and its Applications, Vol I (Wiley, 1968), Chapter III, page 89, deals with this (and many related) problems. Chapter II deals with the simple random walk S_k = X_1 + X_2 + ... + X_k, where the X_i are iid and X_i = +-1 with prob. 1/2 each.
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> On page 89 Feller states and proves Theorem 1: "The probability that the maximum of a path of length n equals r >= 0 coincides with the positive member of the pair p(n,r) and p(n,r+1).
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> Earlier in Chapter he gave the formula p(n,k)= Pr{S_n = k} = C(n,(n+k)/2)/2^n, where C(u,v) denotes the binomial coefficient "u choose v".
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>
> The answer to your "<= m" question is the sum of those probabilities for r from 0 to m, plus the probability that the max is < 0. The latter can be obtained from the expression on page 77, which is
>
> P{S_1 > 0, S_2 > 0, ... S_2n > 0} = (1/2)* u(2n),
>
> and where u(2j) = C(2j,j)/2^(2j) = P{S_2j = 0}. Note that having all S_i < 0 has the same probability as having all S_i > 0.





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