Solving Binomial Dist. Exercise with n=64 & p=0.2 - Help Needed!

  • Thread starter wiz0r
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In summary: That's not what the problem asks for. The problem asks for the probability that no passenger gets bumped.Thanks for the input!In summary, the problem asks for the probability that no passenger gets bumped, which is 0.030260441.
  • #1
wiz0r
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The exercisie is in the attachment.

I am trying to solve it using a Binomial distribution, using n = 64, and p = 0.2.

P(X=1) =

(64) (0.2)^1 (0.8)^63
( 1)

and, I get that P(X=1) = 1.00434 * 10^-5

However, this does not seems correct, can anyone help me here?? I need to submit this in 4hours, so please help me. Thanks.
 

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  • #2
Could the answer be: 0.030260441?
 
  • #3
How did you calculate that number?
 
  • #4
Seems OK to me. As you described it, you're looking for the probability of 1 success in 64 trials, where each trial has a 0.2 probability of success.

Another way to think about this is that you have a jar with 5 balls in it, with one white ball and four black balls. For each trial, you reach in (without looking) and pick out a ball and record its color, then put the ball back in. If you do this 64 times, what's the probability that you get 1 white ball out of 64 trials? It's pretty low.
 
  • #5
wiz0r said:
The exercisie is in the attachment.

I am trying to solve it using a Binomial distribution, using n = 64, and p = 0.2.

P(X=1) =

(64) (0.2)^1 (0.8)^63
( 1)

and, I get that P(X=1) = 1.00434 * 10^-5

However, this does not seems correct, can anyone help me here?? I need to submit this in 4hours, so please help me. Thanks.

Now that I can see your attachment, what you calculated seems correct for P(X = 1), but this isn't the probability that the problem asks for, which is the probability that at least one passenger will get bumped.
 
  • #6
Thanks for the input so far guys:

As for my last attempt:

After I careful read the problem, it says "at least one passenger..", so I assumed that it was either 1 passager needs to be "bumped", or 2, or 3, or 4, or 5, or 6.

So, I added the probabilities of:

P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4) + P(X = 5) + P(X = 6)

And that's how I got the 0.030260441.
 
  • #7
Yes, Mark44! Is it correct now??
 
  • #8
Looks OK, assuming you calculated the individual probabilities correctly. For example, for P(X = 2) you have 64C2*(.2)2*(.8)62, right? (That number at the beginning works out to 64*63/2.)
 
  • #9
Thank you, Mark. I did it with a formula using Excel, so I'm pretty sure it's correct. Thanks a lot!
 
  • #10
Actually, I had an error there, the correct answer is: 0.027605266.

My bad.
 
  • #11
Anyways, now that you've worked it out, it might interest you to know there's a cute shortcut -- what is the probability that nobody gets bumped?
 

1. What is the formula for calculating the binomial distribution when n=64 and p=0.2?

The formula for calculating the binomial distribution is P(x) = (nCx) * p^x * (1-p)^(n-x), where n is the number of trials, p is the probability of success, and x is the number of successes.

2. How do I determine the mean and standard deviation for a binomial distribution with n=64 and p=0.2?

The mean for a binomial distribution is calculated by multiplying n by p, which in this case would be 64 * 0.2 = 12.8. The standard deviation can be found by taking the square root of n * p * (1-p), which would be sqrt(64 * 0.2 * (1-0.2)) = 3.5777.

3. Can I use a calculator to solve binomial distribution exercises?

Yes, most scientific calculators have a function for calculating binomial distributions. You can also use online calculators or statistical software programs.

4. How do I interpret the results of a binomial distribution with n=64 and p=0.2?

The results of a binomial distribution can be interpreted as the probability of getting a certain number of successes (x) in a specified number of trials (n) with a given probability of success (p). So, for n=64 and p=0.2, the results would show the probability of getting 0, 1, 2, 3, etc. successes in 64 trials with a 20% chance of success on each trial.

5. Are there any assumptions or limitations when using the binomial distribution formula?

Yes, the binomial distribution assumes that the trials are independent and that the probability of success remains constant for each trial. It also works best when the number of trials (n) is large and the probability of success (p) is not too close to 0 or 1. Additionally, the binomial distribution may not be appropriate for certain situations, such as when the sample size is not fixed or when the outcome of one trial could affect the outcome of another.

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