Calculating Chances of Success with Binomial Distribution: A Homework Example

In summary, the conversation discusses the use of binomial distribution to calculate the chances of getting a desired outcome (represented by x) out of a given number of attempts (n). The formula x! / y!(x-y)! is mentioned, but it is clarified that the easier approach is to calculate the probability of losing all attempts (represented by P) and then determine the probability of winning (1-P).
  • #1
Schmidtter
1
0

Homework Statement


I am trying to figure out if I have a 20% chance to get what I want (let it = x) and I have 6 chances to do so (n=6), I am curious how I set this question up to find out my chances of getting 'x' once out of the 6 times I try.

Homework Equations


Binomial Distribution.

x! / y!(x - y)!


The Attempt at a Solution



x = 0.2
y = 0.8

= 0.8! / 0.2! (0.8 - 0.2)!
= 40320 / 1440
= 28

Any help would be appreciated.
 
Physics news on Phys.org
  • #2
I don't think you quite get the binomial distribution. What is '.8!' suppose to mean? You might want to review it. On the other hand, the easy way to solve this problem is to figure out your odds of losing 6 straight times, call it P. Then your odds of winning are 1-P.
 
  • #3


I would suggest using the binomial distribution formula to calculate the probability of getting 'x' once out of 6 tries. The formula is P(x) = nCx * px * (1-p)n-x, where n is the number of trials, p is the probability of success, and x is the number of successes. In this case, n = 6, p = 0.2, and x = 1. Plugging these values into the formula, we get P(x) = 6C1 * (0.2) * (1-0.2)6-1 = 6 * 0.2 * 0.8^5 = 0.3932. This means that there is a 39.32% chance of getting 'x' once out of 6 tries with a 20% chance of success each time.
 

FAQ: Calculating Chances of Success with Binomial Distribution: A Homework Example

How do I calculate the probability of success using binomial distribution?

To calculate the probability of success using binomial distribution, you will need to know the number of trials, the probability of success for each trial, and the number of successes you are interested in. You can then use the formula P(x) = (nCx)(px)(qn-x), where n is the number of trials, x is the number of successes, p is the probability of success, and q is the probability of failure (1-p).

What is the difference between binomial distribution and normal distribution?

Binomial distribution is used to calculate the probability of a certain number of successes in a fixed number of trials, while normal distribution is used to calculate the probability of a continuous variable falling within a certain range. Binomial distribution also assumes that each trial is independent, while normal distribution assumes that the data is normally distributed.

How do I know if I can use binomial distribution for my data?

You can use binomial distribution if your data meets the following criteria: (1) the number of trials is fixed, (2) each trial has two possible outcomes (success or failure), (3) the probability of success is the same for each trial, and (4) the trials are independent.

Can binomial distribution be used for large sample sizes?

Yes, binomial distribution can be used for large sample sizes. However, as the sample size increases, the binomial distribution becomes more closely approximated by the normal distribution. This means that for large sample sizes, the results from binomial distribution and normal distribution will be similar.

How can I interpret the results from binomial distribution?

The results from binomial distribution can be interpreted as probabilities. For example, if you calculate a probability of 0.3, this means that there is a 30% chance of getting the desired number of successes in the given number of trials. It is important to note that the results from binomial distribution are not guarantees, but rather the likelihood of a certain outcome occurring.

Similar threads

Back
Top