• N coins flip -- #heads ----- prob. of a tie (as N increases)

    From henhanna@gmail.com@21:1/5 to All on Tue Oct 4 10:46:47 2022
    (Agatha, Beniko)

    A and B have 1 coin each.
    They throw all of their coins and count the number of heads.
    prob. of a tie must be ... 1/2

    A and B have 2 coins each. (...)
    prob. of a tie must be ... (smaller)

    A and B have 3 coins each. (...)
    prob. of a tie must be ... (even smaller)

    (as N increases)

    (1) Is this value going down to zero ?

    (2) The same question, where A has an extra coin.

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Gareth Taylor@21:1/5 to henh...@gmail.com on Tue Oct 4 22:16:10 2022
    In article <2cfbb9cb-bf93-4455-b820-f4c521c5975bn@googlegroups.com>, henh...@gmail.com <henhanna@gmail.com> wrote:

    A and B have 1 coin each.
    They throw all of their coins and count the number of heads.
    prob. of a tie must be ... 1/2

    A and B have 2 coins each. (...)
    prob. of a tie must be ... (smaller)

    A and B have 3 coins each. (...)
    prob. of a tie must be ... (even smaller)

    (1) Is this value going down to zero ?

    I am terrible at probability but here are my immediate thoughts...

    In n flips, the probability of getting k heads is (nCk)/2^n, so the
    probability that they both get k heads is its square.

    Summing over all k (which we can do as the events are disjoint) gives

    [ (nC0)^2 + (nC1)^2 + ... + (nCn)^2 ] / 4^n

    The sum in brackets here equals (2n)Cn.

    (Proof? Use nCk = nC(n-k) and the sum is a convolution.)

    One way to show that (2n)Cn / 4^n tends to 0 is via logs.

    I can fill in the details and steps if needed, but since I've had no
    replies to any of my posts to your questions, I'm unsure that they're
    getting through. So let me know if you'd like steps.

    On the other hand, maybe someone has a _nice_ answer. I'm rubbish at probability.

    Gareth

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From henhanna@gmail.com@21:1/5 to Gareth Taylor on Tue Oct 4 15:01:49 2022
    On Tuesday, October 4, 2022 at 2:16:15 PM UTC-7, Gareth Taylor wrote:
    In article <2cfbb9cb-bf93-4455...@googlegroups.com>,
    henh...@gmail.com <henh...@gmail.com> wrote:

    A and B have 1 coin each.
    They throw all of their coins and count the number of heads.
    prob. of a tie must be ... 1/2

    A and B have 2 coins each. (...)
    prob. of a tie must be ... (smaller)

    A and B have 3 coins each. (...)
    prob. of a tie must be ... (even smaller)

    (1) Is this value going down to zero ?



    I am terrible at probability but here are my immediate thoughts...

    In n flips, the probability of getting k heads is (nCk)/2^n, so the probability that they both get k heads is its square.

    Summing over all k (which we can do as the events are disjoint) gives

    [ (nC0)^2 + (nC1)^2 + ... + (nCn)^2 ] / 4^n

    The sum in brackets here equals (2n)Cn.

    (Proof? Use nCk = nC(n-k) and the sum is a convolution.)

    One way to show that (2n)Cn / 4^n tends to 0 is via logs.

    I can fill in the details and steps if needed, but since I've had no
    replies to any of my posts to your questions, I'm unsure that they're
    getting through. So let me know if you'd like steps.

    On the other hand, maybe someone has a _nice_ answer. I'm rubbish at probability.

    Gareth



    I am terrible at probability but here are my immediate thoughts...

    waht are you good (better) at? do you write Limericks or Sonnets ?



    The sum in brackets here equals (2n)Cn.

    that's a nice one....


    i recently learned of the name [Hockey-stick identity]
    ( but i thik i was vaguely aware of it....)

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Gareth Taylor@21:1/5 to henh...@gmail.com on Tue Oct 4 23:13:56 2022
    In article <828fc0db-e4ce-45e9-9600-bf93594ef524n@googlegroups.com>, henh...@gmail.com <henhanna@gmail.com> wrote:

    I am terrible at probability but here are my immediate thoughts...
    waht are you good (better) at? do you write Limericks or Sonnets ?

    Number theory or algebra is more fun. I teach maths, but I have a bit
    of a mental block for probability. You'll notice that I turned your
    question into combinatorics rather than probability!

    Oddly, I have written silly poems in the past!

    i recently learned of the name [Hockey-stick identity]

    I had to look that up. I know the result but not that name. The result
    I invoked above was an example of Vandermonde's Convolution.

    Gareth

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From henhanna@gmail.com@21:1/5 to Gareth Taylor on Tue Oct 4 15:57:44 2022
    On Tuesday, October 4, 2022 at 2:16:15 PM UTC-7, Gareth Taylor wrote:
    In article <2cfbb9cb-bf93-4455...@googlegroups.com>,
    henh...@gmail.com <henh...@gmail.com> wrote:

    A and B have 1 coin each.
    They throw all of their coins and count the number of heads.
    prob. of a tie must be ... 1/2

    A and B have 2 coins each. (...)
    prob. of a tie must be ... (smaller)

    A and B have 3 coins each. (...)
    prob. of a tie must be ... (even smaller)

    (1) Is this value going down to zero ?
    I am terrible at probability but here are my immediate thoughts...

    In n flips, the probability of getting k heads is (nCk)/2^n, so the probability that they both get k heads is its square.

    Summing over all k (which we can do as the events are disjoint) gives

    [ (nC0)^2 + (nC1)^2 + ... + (nCn)^2 ] / 4^n

    The sum in brackets here equals (2n)Cn.

    (Proof? Use nCk = nC(n-k) and the sum is a convolution.)

    One way to show that (2n)Cn / 4^n tends to 0 is via logs.



    not too surprised that it goes to Zero...


    ( What 's a probability value that (interestingly) Doesn't go to Zero as N increases ? )


    simulation:

    (2-sided) 1 : 0.50003
    (2-sided) 2 : 0.37273
    (2-sided) 3 : 0.31224
    (2-sided) 4 : 0.27469
    (2-sided) 5 : 0.24521
    (2-sided) 6 : 0.22711
    (2-sided) 7 : 0.20843
    (2-sided) 8 : 0.19551
    (2-sided) 9 : 0.18549
    (2-sided) 10 : 0.17606

    (2-sided) 100 : 0.0559
    (2-sided) 1000 : 0.0172

    (2-sided) 10000 : 0.006

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Gareth Taylor@21:1/5 to henh...@gmail.com on Wed Oct 5 00:12:51 2022
    In article <bd470200-70b0-46e7-af4d-cf46bd66f877n@googlegroups.com>, henh...@gmail.com <henhanna@gmail.com> wrote:

    ( What's a probability value that (interestingly) Doesn't go to Zero
    as N increases ? )

    Suppose you have 26 cards labelled from A to Z. You shuffle them and
    then deal them out in a row. What is the probability that none of the
    letters is in the correct position?

    With just two cards, it's obviously 1/2.

    How about three? The orders BCA and CAB have none in the correct
    position, while the orders ACB, CBA, BAC, ACB have at least one in the
    correct position. So it's 1/3.

    What happens for larger alphabets?

    Gareth

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Richard Tobin@21:1/5 to All on Tue Oct 4 23:35:20 2022
    As Gareth Taylor said, the probability of both players getting the
    same number of heads is (2n)Cn / 4^n.

    But (2n)Cn / 4^n is *also* the probability of the two players getting
    exactly n heads between them.

    This is unsurprising as one is

    nC0 . nC0 + nC1 . nC1 + ... + nCn . nCn

    and the other is

    nC0 . nCn + nC1 . nC(n-1) + ... + nCn . nC0

    and nCk = nC(n-k)

    Does anyone have a more intuitive explanation as to why these two
    probabilities are the same?

    -- Richard

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Mike Terry@21:1/5 to Richard Tobin on Wed Oct 5 01:30:16 2022
    On 05/10/2022 00:35, Richard Tobin wrote:
    As Gareth Taylor said, the probability of both players getting the
    same number of heads is (2n)Cn / 4^n.

    But (2n)Cn / 4^n is *also* the probability of the two players getting
    exactly n heads between them.

    This is unsurprising as one is

    nC0 . nC0 + nC1 . nC1 + ... + nCn . nCn

    and the other is

    nC0 . nCn + nC1 . nC(n-1) + ... + nCn . nC0

    and nCk = nC(n-k)

    Does anyone have a more intuitive explanation as to why these two probabilities are the same?


    I'm not sure if this is any more intuitive...

    If A and B both throw n coins and get a tie for heads, then by reversing all of B's coins we would
    get a total of n heads between them. And vice-versa. So if we look at the space of all 2n coin
    tosses, there is a 1-1 correspondence [viz. through reversing B's tosses] which associates each
    "equal heads" outcome to a "n heads total" outcome and vice versa.

    So the count of outcomes for each condition is the same, hence the probabilities are the same
    (dividing the common count by 2^(2n)).

    Mike.

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Phil Carmody@21:1/5 to Mike Terry on Thu Oct 6 15:57:27 2022
    Mike Terry <news.dead.person.stones@darjeeling.plus.com> writes:
    On 05/10/2022 00:35, Richard Tobin wrote:
    As Gareth Taylor said, the probability of both players getting the
    same number of heads is (2n)Cn / 4^n.

    But (2n)Cn / 4^n is *also* the probability of the two players getting
    exactly n heads between them.

    This is unsurprising as one is

    nC0 . nC0 + nC1 . nC1 + ... + nCn . nCn

    and the other is

    nC0 . nCn + nC1 . nC(n-1) + ... + nCn . nC0

    and nCk = nC(n-k)

    Does anyone have a more intuitive explanation as to why these two
    probabilities are the same?

    I'm not sure if this is any more intuitive...

    If A and B both throw n coins and get a tie for heads, then by
    reversing all of B's coins we would get a total of n heads between
    them. And vice-versa. So if we look at the space of all 2n coin
    tosses, there is a 1-1 correspondence [viz. through reversing B's
    tosses] which associates each "equal heads" outcome to a "n heads
    total" outcome and vice versa.

    So the count of outcomes for each condition is the same, hence the probabilities are the same (dividing the common count by 2^(2n)).

    Perfect!

    Phil
    --
    We are no longer hunters and nomads. No longer awed and frightened, as we have gained some understanding of the world in which we live. As such, we can cast aside childish remnants from the dawn of our civilization.
    -- NotSanguine on SoylentNews, after Eugen Weber in /The Western Tradition/

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From henhanna@gmail.com@21:1/5 to Phil Carmody on Thu Oct 6 09:05:49 2022
    On Thursday, October 6, 2022 at 5:57:29 AM UTC-7, Phil Carmody wrote:
    Mike Terry <news.dead.p...@darjeeling.plus.com> writes:
    On 05/10/2022 00:35, Richard Tobin wrote:
    As Gareth Taylor said, the probability of both players getting the
    same number of heads is (2n)Cn / 4^n.

    But (2n)Cn / 4^n is *also* the probability of the two players getting
    exactly n heads between them.

    This is unsurprising as one is

    nC0 . nC0 + nC1 . nC1 + ... + nCn . nCn

    and the other is

    nC0 . nCn + nC1 . nC(n-1) + ... + nCn . nC0

    and nCk = nC(n-k)

    Does anyone have a more intuitive explanation as to why these two
    probabilities are the same?



    I'm not sure if this is any more intuitive...

    If A and B both throw n coins and get a tie for heads, then by
    reversing all of B's coins we would get a total of n heads between
    them. And vice-versa. So if we look at the space of all 2n coin
    tosses, there is a 1-1 correspondence [viz. through reversing B's
    tosses] which associates each "equal heads" outcome to a "n heads
    total" outcome and vice versa.

    So the count of outcomes for each condition is the same, hence the probabilities are the same (dividing the common count by 2^(2n)).


    Perfect!

    Phil
    --


    1. i wonder what is another example of ... looking in a novel way to show that two problems are actually the same


    2. What else is (2n C n) the answer for ?

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)