Solving Discrete Distribution: P(X = 0 & 1)

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    Discrete Distribution
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Discussion Overview

The discussion revolves around generating a random variable X that takes values 0 and 1 with equal probability using a biased coin. Participants explore the method of flipping the coin multiple times until two consecutive flips yield different results, and they aim to establish the probabilities P(X = 0) and P(X = 1).

Discussion Character

  • Exploratory
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant seeks assistance in demonstrating that P(X = 0) = P(X = 1) using a biased coin with heads probability p.
  • Another participant notes that to proceed past a certain step, one must have one head and one tail from the two flips, suggesting that this leads to two equiprobable outcomes.
  • A participant expresses understanding that P(X = 0) is equal to 1/2 but requests a detailed derivation of this probability.
  • One participant calculates that the probability of reaching the step where X is determined is 2p(1-p), leading to the conclusion that P(X = 0) = P(X = 1) = 1/2.
  • A participant proposes a potentially simpler method of continuously flipping the coin until the last two results differ, assigning values to X based on the final flip.
  • Another participant counters the proposed simpler method, arguing that sequences of flips leading to different outcomes have different probabilities and that the original method must be followed.

Areas of Agreement / Disagreement

Participants express differing views on the proposed methods for generating the random variable X. While some calculations suggest that P(X = 0) and P(X = 1) are equal, there is no consensus on the simplicity or validity of alternative methods presented.

Contextual Notes

Participants have not resolved the implications of using a biased coin in the proposed methods, and there are assumptions regarding the independence of coin flips that remain unexamined.

Somefantastik
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I need help getting started on this.

Want to generate a random variable X, equally likely 0, 1, using biased coin (heads probability p).

1. Flip coin, result is labled [tex]0_{1}[/tex]
2. Flip coin, result is labeled [tex]0_{2}[/tex]
3. [tex]0_{1} = 0_{2}[/tex]=> return to step 1
4. [tex]0_{2}[/tex]= heads => X = 0, [tex]0_{2}[/tex] = tails => X = 1

Show X is equally likely to be 0 or 1.

A good place to start would be showing P{X = 0} = P{X = 1}. Can you show me how to find those two probabilities?
 
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In order to get past step 3, you have to have had one head and one tail on the two flips. Since the probs of HT and TH are equal, step 4 will give you 2 equiprobable results.
 
Keeping in mind that this is a biased coin, can someone please show me how to explicitly find P{X = 0}? I understand that it is equal to 1/2 but I need to see how to get there.
 
Prob(HT)=Prob(TH)=p(1-p). Prob(get to step 4) is 2p(1-p), therefore prob(X=0)=prob(X=1)=p(1-p)/(2p(1-p))=1/2.
 
Is there a simpler way to do this where you continuously flip a coin until the last 2 results are different, that sets X = 0 if the final flip is a head, X = 1 if final flip is a tail?
 
Somefantastik said:
Is there a simpler way to do this where you continuously flip a coin until the last 2 results are different, that sets X = 0 if the final flip is a head, X = 1 if final flip is a tail?
No. A sequence of heads followed by one tail has a different probability than a sequence of tails followed by one head. You always need to start fresh as described in your original statement.
 

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