Probability distributions binomial or hypergeometric

In summary, the probability of a committee of 16 persons containing at least 3 women can be approximated using the hypergeometric or binomial distribution. However, the binomial approximation may not be accurate in this case due to the large populations of men and women compared to the sample size.
  • #1
xdrgnh
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Homework Statement


A committee of 16 persons is selected randomly from a group of 400 people, of whom are 240 are women and 160 are men. Approximate the probability that the committe contains at least 3 women.



I just want to know if it's hyper geometric or binomial. I suspect it's hyper geometric because if you pick 1 person from total 400 people you alter the probability of picking the next person thus it's not independent.
 
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  • #2
xdrgnh said:

Homework Statement


A committee of 16 persons is selected randomly from a group of 400 people, of whom are 240 are women and 160 are men. Approximate the probability that the committe contains at least 3 women.



I just want to know if it's hyper geometric or binomial. I suspect it's hyper geometric because if you pick 1 person from total 400 people you alter the probability of picking the next person thus it's not independent.

You are correct. However, in cases where populations of both types are large compared with the total sample size, the hypergeometric and the binomial give nearly the same results, at least if we do not ask for results far out in the 'tails'. In this case, we want 1-P{<= 2 women}, and the '2' is far below the mean. That means that the binomial approximation may not be so good in this case, even though the committee size 16 is small compared to both 160 and 240.
 

Related to Probability distributions binomial or hypergeometric

1. What is the difference between binomial and hypergeometric distributions?

The main difference between binomial and hypergeometric distributions is the sampling method used. Binomial distributions involve independent trials with a fixed number of trials, while hypergeometric distributions involve sampling without replacement from a finite population.

2. What types of events can be modeled using a binomial distribution?

Binomial distributions can be used to model events with a binary outcome (i.e. success or failure) that have a fixed number of trials and a constant probability of success for each trial. Examples include flipping a coin, rolling a die, or testing a product for defects.

3. How is the mean of a binomial distribution calculated?

The mean of a binomial distribution is calculated by multiplying the number of trials (n) by the probability of success (p). This can also be written as np, where n is the sample size and p is the probability of success for each trial.

4. Can a hypergeometric distribution be used for large sample sizes?

No, hypergeometric distributions are only applicable for small sample sizes (usually less than 10% of the population size). For large sample sizes, a binomial distribution can be used as an approximation.

5. How can I determine the probability of a specific outcome using a probability distribution?

To determine the probability of a specific outcome, you can use the probability mass function (PMF) for discrete distributions such as binomial and hypergeometric. For continuous distributions, the probability is represented by the area under the curve in a specific interval. Alternatively, you can use statistical software or tables to find the probability of a specific outcome.

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