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rogo0034
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Homework Statement
I worked out A) just fine it seems (given the answer in the book), but B) I'm not sure how to take this out. Below was a try but I'm not sure i was even on the right track. Any ideas?
rogo0034 said:Anyone have any ideas here?
rogo0034 said:ok, I answered my own question. the last two i added in would not work due to the criteria. so i guess you helped, thanks RGV. I'll try and find a better format to post these in.
The Multivariate Hypergeometric Distribution is a probability distribution used to calculate the probability of obtaining a specific combination of outcomes from a sample of multiple categories, when drawing without replacement.
The Multivariate Hypergeometric Distribution is a special case of the Multinomial Distribution, where the sample size is smaller than the population size. In other words, the Multivariate Hypergeometric Distribution is used when sampling without replacement, whereas the Multinomial Distribution is used when sampling with replacement.
The formula for calculating the Multivariate Hypergeometric Distribution is: P(x1, x2, ..., xn) = (N1C1)(N2C2)...(NnCn) / NtotalCtotal, where N1, N2, ..., Nn represent the number of items in each category, and x1, x2, ..., xn represent the number of items sampled from each category.
The Multivariate Hypergeometric Distribution is commonly used in genetics to study the frequency of different alleles in a population. It is also used in quality control to determine the probability of a certain number of defective items in a sample from a production line.
The Multivariate Hypergeometric Distribution assumes that the population size is much larger than the sample size. It also assumes that each item in the population is equally likely to be selected, and that the samples are drawn without replacement. These assumptions may not always hold true in real-life situations, making the Multivariate Hypergeometric Distribution less accurate.