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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 13 taken from a population of size 47, in which there are 37 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 13 people from its workforce of 47. (In this workforce, only 37 of those 47 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 negative skew (left skew), that its sample space is integers between 3 and 13, inclusive. In other words, S = {3, 4, 5, …, 13}.
Here is the probability function of the Hypergeometric distribution described in the example:
Continuing the candy example, let us determine the probability that exactly 9 people in the survey respond that they like the candies. In symbols, calculate P[X = 9].
In the box below, please enter the value of P[X = 9], where X ~ H(n=13, N=47, K=37), then click on the “Check your answer!” button. Please round your answer to the ten-thousandths place.
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