Probability of 5 Heads in Binomial Distribution

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Discussion Overview

The discussion revolves around calculating the probability of obtaining 5 heads when flipping a 4-sided coin 5 times, exploring the application of binomial distribution principles. Participants examine different expressions for probability and their equivalence, as well as the implications of event likelihood.

Discussion Character

  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant presents a formula for the probability of getting 5 heads using binomial distribution, suggesting two expressions for probability calculations.
  • Another participant argues that the two expressions are not equivalent, citing that the events are not equally likely in the case of a weighted coin.
  • A third participant points out the assumption of equal probability for each side of the coin, indicating a misunderstanding in the initial setup.
  • A later reply corrects the initial expressions, stating that if only one side of the coin is heads, the probability of getting 5 heads simplifies to (0.25)^5 or 1/(4^5), questioning the inclusion of the number 10 in the original formula.

Areas of Agreement / Disagreement

Participants express disagreement regarding the equivalence of the two probability expressions and the assumptions about the coin's sides. The discussion remains unresolved as different interpretations and corrections are presented.

Contextual Notes

There are limitations in the assumptions regarding the coin's sides and the applicability of the binomial distribution in this context. The discussion highlights the need for clarity on event likelihood and the definitions used in probability calculations.

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Suppose you have a coin with 4 fair sides, flip it 5 times, and want to know the probability of 5 heads. This is
K(10,5) * (0.25)5 * (1-0.25)5 = K(10,5)*0.255*0.755
Or more generally for any binomially distributed outcome:

1) p(x=r) = pr*(1-p)n-r*K(n,r)

But also we must have that:

2) p(x=r) = K(n,r)/total combinations = K(n,r)/4n
How do you show that 1) and 2) are equivalent?
 
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They're not equivalent. Your concept in 2) is not applicable in this case because the events are not equally likely.

Take for example a single coin flip of a fair coin where p=1-p=1/2. The probability of heads is the number of events resulting in heads divided by the total number of possible outcomes or 1/2. All events are equally likely. Now consider a weighted coin where p=3/4=p(heads). The number of ways to get heads is still 1 and the total number of possible outcomes is still 2 but p(heads) does not equal 1/2.
 
hmm...

you were to suppose that each side was equally probable :)
 
Ooops, I'm really sorry, you have a 4 side coin. My bad.

Anyway, your expressions are incorrect. I'm assuming only one side of the coin is heads. In that case, the probability of 5 heads is (0.25)^5=(1/4)^5.

Alternatively, the number of ways to get 5 heads is 1 and the number of possible outcomes is 4^5, so P(5 heads)=1/(4^5). Same result. Where did the 10 come from?
 

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