Showing Chi squared is independent with another variable

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The discussion revolves around determining the independence of variables Y and Z, where Y is defined as Y=X1^2 + X2^2, indicating a chi-squared distribution with 2 degrees of freedom. The challenge lies in finding the distribution of Z=X1/(X1^2 + X2^2) without using the Jacobian method. It is argued that Y and Z are not independent, as algebraic manipulation shows Y can be expressed in terms of Z. However, the discussion highlights that merely finding a relationship between Y and Z does not conclusively prove dependence, referencing an example where Y and Z can be independent despite a combined expression. The conversation suggests exploring polar coordinates for further insights into the relationship between these variables.
torquerotates
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So I have X1 and X2 are iid standard normal.

Then I have Y=X1^2+ X2^2

and

Z=X1/(X1^2+x2^2)

I'm supposed to find the distribution of Y and Z and then determine if they are independent.

Clearly Y is chi squared with degrees of freedom 2.

But I have no idea how to find the distribution of Z. I know there is a shortcut without using the jacobian, like I did with the Chi Squares, but I'm not sure how to do it.
I know Y and Z are not independent because with some algebra,

Y=Y*Z^(2)+X2
So Y depends on Z and vice versa, therefore they cannot be independent. Is that true?
 
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(I moved this thread to the homework section)

I could be interesting to go to polar coordinates (in the X1-X2-plane).

Just finding an equation where Y and Z appear is not sufficient to show a dependence.
Imagine Y=X1, Z=X2, then Y+Z=X1+X2 but they are clearly independent.
 
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