Coint toss probability question

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In summary, there are two attempts at finding the probability of obtaining exactly one head out of three coin tosses when at least one head is obtained. The first attempt uses brute force to find that there are 3 possible combinations out of 7 total combinations, giving a probability of 3/7. The second attempt uses a flawed method of assuming independence between events when they are not, resulting in a probability of 3/4 instead of 3/7. A better method would be to use the concept of random variables and the Binomial distribution, which gives a probability of 3/7 as well.
  • #1
fraggle
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Homework Statement


A coin is tossed 3 times. at least 1 head is obtained. Determine the probability that exactly 1 head is obtained



Homework Equations





The Attempt at a Solution



brute force indicates that there 7 possible combinations:

HHH, HHT, HTH, HTT, THH, THT, TTH (because at least one heads is obtained).

Out of these we see that there are 3 occasions where there is exactly one heads.
If we let S be the sample space of all possable outcomes, and let E be the event of having exactly one heads, then a basic rule of probability indicates that the probability P(E)=|E|/|S|=3/7.

However, using another method:
fix one coin throw's result as heads. Then the probability of the other two throws being tails is (1/2)(1/2)=1/4.
Since we can fix heads 3 times, this indicates that the probability is 3(1/4)=3/4.

Can anyone spot where the flaw is in either of these attempts at a solution?
thanks
(this isn't a homework question btw)
 
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  • #2
3/7 is when you drop "at least 1 head is obtained" out
1/4 is when when "at least 1 head is obtained" and that is the only head obtained
 
  • #3
fraggle said:
However, using another method:
fix one coin throw's result as heads. Then the probability of the other two throws being tails is (1/2)(1/2)=1/4.
Since we can fix heads 3 times, this indicates that the probability is 3(1/4)=3/4.
You can't do that. Probabilities add only if the underlying events are mutually exclusive events in the same parent population. That isn't the case here.
 
  • #4
housemartin said:
3/7 is when you drop "at least 1 head is obtained" out
1/4 is when when "at least 1 head is obtained" and that is the only head obtained


Can you please explain?
 
  • #5
I think the flaw (in the second attempt) is the following:

You summed the probabilities of events {HTT}, {THT} and {TTH} because they are disjoint events whose union is the event targeted. The error was to consider each of them as intersections of two equally likely, independent events whose probability is 1/2 (getting two tails).
Rather, they are individual instances of a sample space with equally likely 7 elements as you deduced directly. So their probabilities are 1/7 and the desired probability equals 3(1/7)=3/7.

Have you learned random variables? If you have, I guess there's an easier way to do this exercise. Let X denote the number of heads in the three throws. Then, as each of the 3 throws is independent and the probability of obtaining a head in each of them remains constant and equal to 1/2, X is Binomial with parameters n=3 and p=1/2. The desired probability is then

[tex]P(X=1|X\geq 1)=\frac{P(X=1,X\geq 1)}{P(X\geq 1)}=\frac{P(X=1)}{1-P(X=0)}.[/tex]

But since [tex]P(X=k)={n \choose k}p^k(1-p)^{n-k}[/tex] for a Binomial variable, we have [tex]P(X=0)=1/8[/tex] and [tex]P(X=1)=3/8[/tex]. So,

[tex]P(X=1|X\geq 1)=\frac{3/8}{1-1/8}=\frac{3/8}{7/8}=\frac{3}{7}.[/tex]

Notice the comma in [tex]P(X=1,X\geq 1)[/tex] means intersection.
 
  • #6
hellofolks said:
I think the flaw (in the second attempt) is the following:

You summed the probabilities of events {HTT}, {THT} and {TTH} because they are disjoint events whose union is the event targeted. The error was to consider each of them as intersections of two equally likely, independent events whose probability is 1/2 (getting two tails).
Rather, they are individual instances of a sample space with equally likely 7 elements as you deduced directly. So their probabilities are 1/7 and the desired probability equals 3(1/7)=3/7.

Have you learned random variables? If you have, I guess there's an easier way to do this exercise. Let X denote the number of heads in the three throws. Then, as each of the 3 throws is independent and the probability of obtaining a head in each of them remains constant and equal to 1/2, X is Binomial with parameters n=3 and p=1/2. The desired probability is then

[tex]P(X=1|X\geq 1)=\frac{P(X=1,X\geq 1)}{P(X\geq 1)}=\frac{P(X=1)}{1-P(X=0)}.[/tex]

But since [tex]P(X=k)={n \choose k}p^k(1-p)^{n-k}[/tex] for a Binomial variable, we have [tex]P(X=0)=1/8[/tex] and [tex]P(X=1)=3/8[/tex]. So,

[tex]P(X=1|X\geq 1)=\frac{3/8}{1-1/8}=\frac{3/8}{7/8}=\frac{3}{7}.[/tex]

Notice the comma in [tex]P(X=1,X\geq 1)[/tex] means intersection.

Thanks a lot, that made sense.
 

Related to Coint toss probability question

What is a coin toss probability question?

A coin toss probability question is a type of mathematical problem that involves determining the likelihood or chance of a certain outcome when flipping a coin. It typically involves determining the probability of getting a specific result, such as heads or tails, after a certain number of coin tosses.

How do you calculate the probability of a coin toss?

The probability of a coin toss is calculated by dividing the number of desired outcomes by the total number of possible outcomes. For example, if you want to know the probability of getting heads when flipping a coin, you would divide the number of heads outcomes (1) by the total number of possible outcomes (2), resulting in a probability of 1/2 or 50%.

What is the probability of getting three heads in a row when flipping a coin?

The probability of getting three heads in a row when flipping a coin is 1/8 or 12.5%. This is because the probability of getting a heads on each individual toss is 1/2, and the probability of getting three heads in a row is calculated by multiplying the individual probabilities together (1/2 x 1/2 x 1/2 = 1/8).

How does the number of coin tosses affect the probability?

The more coin tosses that are performed, the closer the probability will be to the theoretical probability of 1/2 or 50%. For example, if you flip a coin 10 times, you may get 6 heads and 4 tails. But if you flip a coin 100 times, you are more likely to get closer to 50 heads and 50 tails, which is the expected theoretical probability.

Can the probability of a coin toss change?

No, the probability of a coin toss will always be 1/2 or 50%. Each individual coin toss is independent of the previous tosses and does not affect the probability of future tosses. This means that no matter how many times you flip a coin, the probability of getting heads will always be 1/2.

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