Find conditional probability mass function

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Homework Help Overview

The discussion revolves around finding the conditional probability mass function for random variables X and Y, which are defined in terms of U1 and U2. Participants are exploring the relationships between these variables and the conditions under which they hold, particularly focusing on the case where X is fixed and its implications for Y.

Discussion Character

  • Exploratory, Assumption checking, Conceptual clarification

Approaches and Questions Raised

  • Participants are attempting to define the joint probability P(X=x, Y=y) and are questioning the complexity of their approaches. There are discussions about the possible values of U1 and U2 given a fixed X, and how these relate to the conditional distribution of Y.

Discussion Status

Some participants are seeking clarification on the relationships between the variables and the probabilities associated with different combinations of U1 and U2. There is an ongoing exploration of specific cases, such as when X=9, to better understand the conditional distributions.

Contextual Notes

Participants are working under the assumption that X and Y are functions of U1 and U2, with specific conditions applied to their values. There is a focus on conditional probabilities and the implications of fixing X on the distribution of Y.

psie
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Homework Statement
Consider a fair die thrown twice. Let ##U_1## be the dots on the first throw and ##U_2## on the second (intuitively, they are independent). Let ##X=U_1+U_2## and ##Y=\min(U_1,U_2)##. Find the conditional probability (mass) function ##p_{Y|X=x}(y)## and the conditional distribution ##F_{Y|X=x}(y)##.
Relevant Equations
We have $$p_{Y|X=x}(y)=\frac{p_{X,Y}(x,y)}{p_X(x)}=\frac{p_{X,Y}(x,y)}{\sum_z p_{X,Y}(x,z)},$$and $$F_{Y|X=x}(y)=\frac{\sum_{z\leq y}p_{X,Y}(x,z)}{p_X(x)}=\frac{\sum_{z\leq y} p_{X,Y}(x,z)}{\sum_z p_{X,Y}(x,z)}.$$
I don't really know how to approach this problem, but my plan is to find ##p_{X,Y}(x,y)=P(X=x,Y=y)##. The two conditions ##X=x## and ##Y=y## in terms of ##U_1## and ##U_2## read (I think) $$U_1=y,U_2 = x-y \text{ or }U_2 = y, U_1 = x-y,\qquad x\geq 2y.$$ So $$P(X = x, Y = y) = \begin{cases} P(U_1 = y, U_2 = x-y\text{ or }U_2 = y, U_1 = x-y) & x\geq 2y \\ 0 & x < 2y\end{cases}.$$ I don't know how to proceed and find ##p_{Y|X=x}(y)##.
 
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I think you are severely overcomplicating things. Both ##X## and ##Y## are functions of ##U_1## and ##U_2## whose probability distributions are very simple. For a given ##X = x##, what are the possible values of ##U_1## and ##U_2##? What are the probabilities of each combination? What does this mean for ##Y##?
 
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Orodruin said:
I think you are severely overcomplicating things. Both ##X## and ##Y## are functions of ##U_1## and ##U_2## whose probability distributions are very simple. For a given ##X = x##, what are the possible values of ##U_1## and ##U_2##? What are the probabilities of each combination? What does this mean for ##Y##?
I appreciate the reply, but I feel very hopeless about this. If we fix an ##x##, then the possible values of ##U_1,U_2## are ##U_1=y,U_2=x-y## or ##U_2=y,U_2=x-y##, and we want ##x\geq 2y##. But then I'm just getting back into what I did above. Could you elaborate on your approach a bit more? Maybe show how you would obtain the conditional pmf, and from there I can see if I can either modify my approach or go with yours.
 
psie said:
Could you elaborate on your approach a bit more?

Please try to answer the questions I posed in the previous post. You only answered the first:
Orodruin said:
For a given ##X = x##, what are the possible values of ##U_1## and ##U_2##?

The second and third are very significant:
Orodruin said:
What are the probabilities of each combination? What does this mean for ##Y##?
Edit: Note: I am talking about the probabilities conditioned on ##X = x## here. It is the only thing you need to look at.
 
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Here is an illustration to help your thought process:
1718746744453.png

If the general case is too hard to start with, focus on this special case of x = 9. What are the conditional distributions of ##U_1## and ##U_2##. Can you fill out the values of ##Y## in this square? What is the conditional probability to find ##Y = 4##?
 
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psie said:
If we fix an ##x##, then the possible values of ##U_1,U_2## are ##U_1=y,U_2=x-y## or ##U_2=y,U_2=x-y##, and we want ##x\geq 2y##.

Ok, i just reread this and realized it actually did not really answer my first question either. The first question asks what is the possible combinations of ##U_1## and ##U_2## given ##X = x##. The value of ##Y## does not enter into the question, just the conditioning on ##X##.
 
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Orodruin said:
Here is an illustration to help your thought process:
View attachment 347103
If the general case is too hard to start with, focus on this special case of x = 9. What are the conditional distributions of ##U_1## and ##U_2##. Can you fill out the values of ##Y## in this square? What is the conditional probability to find ##Y = 4##?
Ok, thank you for elaborating. I don't see the general case right now. In this special case, the conditional pmf of ##U_1## and ##U_2## are, I believe, ##\frac14## (since ##3,4,5## and ##6## have equal probability of appearing). The values of ##Y## are ##3## or ##4##, also with equal probability, so the conditional probability must be ##\frac12## to find ##Y=4## given ##X=9##. Is this correct?
 
Last edited:
psie said:
the conditional probability must be 1/2 to find Y=4 given X=9. Is this correct?
Yes. Even values of X are a little trickier.
 
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haruspex said:
Yes. Even values of X are a little trickier.
Although still not very tricky …
 

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