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Hypergeometric Distributions
Let X be a random variable following a Hypergeometric distribution. All Hypergeometric distributions have three parameters: sample size, population size, and number of successes in the population. For this problem, let X be a sample of size 7 taken from a population of size 37, in which there are 12 successes. An example of where such a distribution may arise is the following:
Statistics, Inc., wants to determine how well the people like its candies. To determine this, they randomly select 7 people from its workforce of 37. (In this workforce, only 12 of those 37 actually like the candies.) Let X be the number of employees surveyed who like the candies.
From the description, we can tell that X has a Hypergeometric distribution. We know this because X is the number of successes in a finite population where subjects cannot be measured more than once.
For those who like pictures, here is a graphic of the probability mass function of X. Note that it has a positive skew (right skew), that its sample space is integers between 0 and 7, inclusive. In other words, S = {0, 1, 2, …, 7}.
Here is the probability function of the Hypergeometric distribution described in the example:
Continuing the candy example, let us determine the probability that exactly 7 people in the survey respond that they like the candies. In symbols, calculate P[X = 7].
In the box below, please enter the value of P[X = 7], where X ~ H(n=7, N=37, K=12), then click on the “Check your answer!” button. Please round your answer to the ten-thousandths place.
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