Multivariate Hypergeometric Distribution

In summary, the conversation is about a homework question that involves finding cases that meet certain criteria. The person asking the question initially provides a solution for part A, but is unsure about part B. They ask for help and receive a response pointing out that they may have missed some cases in their solution. After further discussion, they realize their solution for part B is correct and thank the person for their input.
  • #1
rogo0034
37
0

Homework Statement


CQeI0.png


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?

Homework Equations


x5s6D.png



The Attempt at a Solution


0oC3c.jpg
 
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  • #2
Anyone have any ideas here?
 
  • #3
really, with over 400 views? no know can tackle this? Even Reddit at least took a shot at it. come on boys! lol, anything to get me started thinking right about this would help!
 
  • #4
rogo0034 said:
Anyone have any ideas here?

In (b) you seem to have forgotten the cases (2,2,0,0), (0,2,0,2) and (2,0,0 2). Otherwise the basics are OK (but please in future try to attach more readable files: yours is incomprehensible on my laptop and on my i-phone; it shows up only on my desktop machine.)

RGV
 
Last edited:
  • #5
"All nationalities but Italian are represented" So those three do not comply. It must have a zero for the third space, and contain at least one from each of the others, and must equal 4.
 
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  • #6
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.
 
  • #7
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.

Sorry, I mis-read question (b). Your original solution is correct, and did not leave anything out (as I had erroneously suggested).

RGV
 
  • #8
Thanks for looking at it regardless! This site has helped me so much, I appreciate anyone's input!
 

What is the Multivariate Hypergeometric Distribution?

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.

How is the Multivariate Hypergeometric Distribution different from the Multinomial Distribution?

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.

What is the formula for calculating the Multivariate Hypergeometric Distribution?

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.

What are some real-life applications of the Multivariate Hypergeometric Distribution?

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.

What are the limitations of the Multivariate Hypergeometric Distribution?

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.

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