The Probability of a Biased Coin: n Flips, m Heads

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In summary, the probability of getting a head on flipping a biased coin is p. the coin is flipped n times producing a sequence containing m heads and (n-m) tails what is the probability of obtaining this sequence from n flips.
  • #1
markosheehan
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the probability of getting a head on flipping a biased coin is p. the coin is flipped n times producing a sequence containing m heads and (n-m) tails what is the probability of obtaining this sequence from n flips.
i can't understand the wording
 
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  • #2
I've moved this thread since our advanced forum is for calculus based stats.

A few things we need to observe:

The probability of getting heads is:

\(\displaystyle P(H)=p\)

Now, we know that it is certain that we will either get heads or tails, so we may state:

\(\displaystyle P(H)+P(T)=1\implies P(T)=1-P(H)=1-p\)

So, the probability of getting $m$ heads is:

\(\displaystyle P\left(H_m\right)=p^m\)

And the probability of getting $n-m$ tails is:

\(\displaystyle P\left(T_{n-m}\right)=(1-p)^{n-m}\)

Next we need to look at the number $N$ of ways to choose $m$ from $n$:

\(\displaystyle N={n \choose m}\)

Can you put all this together to find the requested probability?
 
  • #3
when i put this all together i get (n ncr m)*p*(1-p)^n-m however at the back of the book it says the answer is p^m(1-p)^n-m
 
  • #4
What I get is:

\(\displaystyle P(X)={n \choose m}p^m(1-p)^{n-m}\)

And this agrees with the binomial probability formula. :D

This is the probability of getting any sequence with $m$ heads, for any particular such sequence, then it would be:

\(\displaystyle P(X)=p^m(1-p)^{n-m}\)
 
  • #5
markosheehan said:
when i put this all together i get (n ncr m)*p*(1-p)^n-m however at the back of the book it says the answer is p^m(1-p)^n-m
Was it possible that the problem asked for the probability of m heads in a row followed by n-m tails in a row? As MarkFl said, that probability if for any particular such sequence- "m heads in a row followed by n- m tails in a row" or "n- m tails in a row followed by m heads in a row" or "A head, then a tail, then a head, followed by m- 2 heads in a row, followed by n- m- 1 tails in a row", etc.
 

FAQ: The Probability of a Biased Coin: n Flips, m Heads

What is a biased coin?

A biased coin is a coin that has a higher probability of landing on one side compared to the other. This means that the outcomes of the coin toss are not equally likely.

How do you determine the probability of a biased coin?

The probability of a biased coin can be determined by dividing the number of desired outcomes (such as heads) by the total number of possible outcomes. For example, if a coin is biased to land on heads 70% of the time, the probability of getting heads is 0.7 or 70%.

How does the number of flips affect the probability of getting m heads?

The more flips you do, the closer the actual results will be to the expected probability. For example, if a coin is biased to land on heads 70% of the time, the more flips you do, the closer you will get to 70% of the flips resulting in heads.

Can the probability of a biased coin change over time?

Yes, the probability of a biased coin can change over time. This can happen due to external factors such as wear and tear on the coin, or if the coin is intentionally altered.

How does the probability of a biased coin compare to a fair coin?

The probability of a biased coin will always be different from a fair coin, where the probability of getting heads or tails is equal. A fair coin has a probability of 0.5 or 50% for both heads and tails, while a biased coin will have different probabilities for each outcome.

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