Complicated probability question with urns and balls

In summary: So J and M both draw i balls is[(n choose i) * (n choose k - i) / (2n choose k)] * [(m choose i) * (m choose k - i) / (2m choose k)]
  • #1
zeion
466
1

Homework Statement



Suppose that Joe draws k balls from and urn containing n red balls and n green balls, without replacing the balls after they are drawn. Similarly, Mary draws k balls from an urn containing m red balls and m green balls, without replacing the balls after they are drawn. We want to computer the probability that Joe and Mary will draw the same number of red balls.

Homework Equations





The Attempt at a Solution



Let E be the event that J and M draw the same number of red balls.
So P(E) = P(J draws i red balls and M draws i red balls)
= P(J draws i red balls) P(M draws i red balls)

I don't know how to write P(J draws i red balls)
 
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  • #2
zeion said:

Homework Statement



Suppose that Joe draws k balls from and urn containing n red balls and n green balls, without replacing the balls after they are drawn. Similarly, Mary draws k balls from an urn containing m red balls and m green balls, without replacing the balls after they are drawn. We want to computer the probability that Joe and Mary will draw the same number of red balls.

Homework Equations





The Attempt at a Solution



Let E be the event that J and M draw the same number of red balls.
So P(E) = P(J draws i red balls and M draws i red balls)
= P(J draws i red balls) P(M draws i red balls)

I don't know how to write P(J draws i red balls)

Look up the hypergeometric distribution. See, eg.,
http://en.wikipedia.org/wiki/Hypergeometric_distribution or
http://stattrek.com/lesson2/hypergeometric.aspx .

RGV
 
  • #3
the chance that J will draw i red ball is

(n choose i) * (n choose k - i) / (2n choose k)

is that right
 
  • #4
zeion said:
the chance that J will draw i red ball is

(n choose i) * (n choose k - i) / (2n choose k)

is that right

Yes.

RGV
 
  • #5
so J and M both draw i balls is

[(n choose i) * (n choose k - i) / (2n choose k)] * [(m choose i) * (m choose k - i) / (2m choose k)]

right
 

What is the concept of urns and balls in probability?

Urn and balls is a concept commonly used in probability theory to represent a situation where objects are selected at random from a set. An urn represents a container and the balls represent the objects inside the container. The probability of selecting a particular ball is influenced by the number of balls and the number of each type of ball inside the urn.

What is an urn model?

An urn model is a mathematical representation of a situation where objects are drawn at random from a population. It involves using an urn to represent the population and balls to represent the objects in the population. This model is commonly used in probability theory to calculate the probability of selecting a specific object from a given population.

What is the difference between sampling with replacement and sampling without replacement?

Sampling with replacement means that each time an object is selected from an urn, it is put back before the next selection is made. This means that the number of objects in the urn does not change throughout the sampling process. On the other hand, sampling without replacement means that objects are not put back into the urn after they are selected. This decreases the total number of objects in the urn and can affect the probability of selecting certain objects.

How do you calculate the probability of selecting a specific ball from an urn?

The probability of selecting a specific ball from an urn can be calculated by dividing the number of balls of that type in the urn by the total number of balls in the urn. For example, if there are 20 red balls and 80 blue balls in an urn, the probability of selecting a red ball would be 20/100 or 0.2.

How can you apply urn models to real-life situations?

Urn models can be applied to real-life situations such as market research, polling, and epidemiology. For example, in market research, an urn model can be used to estimate the probability of a certain product being purchased by a particular demographic. In polling, an urn model can be used to estimate the probability of a specific candidate winning an election. In epidemiology, an urn model can be used to estimate the probability of a certain disease occurring in a population.

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