Number of Possible Outcomes w/ Restrictions (Coin Toss)

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Discussion Overview

The discussion revolves around determining the total number of possible outcomes in a coin toss system with specific restrictions on the frequency of outcomes over multiple generations. The focus is on theoretical and mathematical reasoning related to probability and combinatorics, particularly in the context of a personal project involving coin tosses.

Discussion Character

  • Exploratory
  • Mathematical reasoning
  • Technical explanation

Main Points Raised

  • One participant describes the need to calculate outcomes for a coin toss system with restrictions on the number of heads and tails over N generations.
  • Another participant suggests summing over the number of heads and setting forbidden summands to zero based on the defined restrictions.
  • A participant requests clarification on the mathematical approach suggested, indicating a lack of familiarity with the concepts involved.
  • One participant provides a detailed example with specific values for x, y, and N, illustrating how to determine the possible number of heads and the corresponding binomial coefficients for valid outcomes.
  • Another participant mentions the potential application of the Chebyshev inequality to derive results related to the problem, referencing the variance of coin tosses.
  • A follow-up question is posed regarding a modified scenario where outcomes affect a starting value, asking how to calculate possible outcomes while maintaining certain boundaries throughout the process.
  • A later reply identifies the modified scenario as a discrete random walk with absorption and references a paper that may relate to the problem.

Areas of Agreement / Disagreement

Participants express various approaches and examples, but there is no consensus on a definitive method or solution to the problem. The discussion includes multiple perspectives and interpretations of the mathematical concepts involved.

Contextual Notes

Some assumptions and definitions regarding the restrictions on outcomes are not fully articulated, and the mathematical steps for calculating outcomes remain unresolved. The discussion also highlights the complexity of the problem as N increases.

ProbQ
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Hey guys,

I am currently working on a personal project, and I've run into a dilemma.

I need to determine the total number of possible outcomes for a coin toss type system, ie two possible outcomes each generation, for N generations. The problem however comes in with the restrictions I have to deal with, these being.

1) Outcome one cannot occur x more times than outcome two.
2) Outcome two cannot occur y more times than outcome one.

Any "branch" of the probability tree that contains such a case needs to be eliminated.

I have no idea how to solve this, besides some form of excel type model with each branch manually calculated, but that looks terribly daunting when the system is allowed to run for many generations.

Any help would be appreciated.
 
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You can sum over the number of "heads", this needs ~N calculations for N coin tosses. Some of those summands are forbidden by your rules, so you can set them to zero.
 
Apologies as I'm pretty uneducated in this field and I'm not quite sure what you mean.

Would you mind elaborating?
 
Let's consider an example: x=y=2, N=60, and I'll call the two outcomes "heads" and "tails".

How many heads can we have?
0? No, we have 60 times tails, that is more than twice the number of heads.
1? No.
...
20? Still not possible, tails would occur twice as often as heads.
21? That is possible
...
39? Possible
40? Not possible, heads would occur twice as often as tails.
...
60? Not possible.

How many ways do we have to get 21 heads in 60 trials? -> Binomial coefficients
How many ways do we have to get 22 heads in 60 trials? -> Binomial coefficients
...
Sum all, and you get the total number.

For large N, it might be useful to find some approximations to simplify the calculation.
 
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I haven't worked on the problem, but the result may follow from manipulating the Chebyshev inequality. Try using the fact that the variance of N tosses of a fair coin has mean N/2 and variance N(p)(1-p) and that you can establish some inequality between 1/x^2 and e^(-x).
 
mfb said:
Let's consider an example: x=y=2, N=60, and I'll call the two outcomes "heads" and "tails".

How many heads can we have?
0? No, we have 60 times tails, that is more than twice the number of heads.
1? No.
...
20? Still not possible, tails would occur twice as often as heads.
21? That is possible
...
39? Possible
40? Not possible, heads would occur twice as often as tails.
...
60? Not possible.

How many ways do we have to get 21 heads in 60 trials? -> Binomial coefficients
How many ways do we have to get 22 heads in 60 trials? -> Binomial coefficients
...
Sum all, and you get the total number.

For large N, it might be useful to find some approximations to simplify the calculation.
Thank you very much, that makes a lot of sense.

I have a further query.

Say if we were to repeat the experiment, flipping coins, and each time we add one or subtract one from a start value, of say a 100, dependent on whether we get heads or tails. Is there a way to find the amount of possible outcomes wherein which the value never reached 200 or 0, throughout the entire process, not just at the end of the run of N coin tosses.

Thanks again.
 
That is a discrete random walk with absorption.
I found this paper, your problem looks like a special case of that.
 

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