Questions about Linear Combinations of Random Variables

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The discussion focuses on the challenges of finding the probability density function (p.d.f.) for the random variable Y, defined as Y=1/2*(X1-X3)^2+1/14*(X2+2X4-3X5)^2. Participants express difficulty in extending their knowledge of moment-generating functions to higher powers of random variables. They note that Z_1 and Z_2, derived from the original variables, are independent and normally distributed. Questions arise about the implications of independence on the distribution of sums or differences of random variables and the treatment of squared variables. The conversation emphasizes the need for understanding transformations of variables in this context.
ken15ken15
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Homework Statement


RQwRhjc.jpg

Homework Equations


Y=1/2*(X1-X3)^2+1/14*(X2+2X4-3X5)^2

The Attempt at a Solution


For (a) part, I have only learned to find the moment-generating function of Y, but not finding the p.d.f.
Moreover, the examples I have seen only involves random variables Xi to the power 1, but not to higher power.

For (b) part, the difficulty for me is just similar to part (a).
 
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Hint: (Z_1^2 + ... +Z_n^2) +(Z_1^2 + ... +Z_m^2) = (Z_1^2 + ... +Z_n^2 +...+ Z_m^2)
 
dirk_mec1 said:
Hint: (Z_1^2 + ... +Z_n^2) +(Z_1^2 + ... +Z_m^2) = (Z_1^2 + ... +Z_n^2 +...+ Z_m^2)

sorry but...what property is it? I haven't learned this before...
 
ken15ken15 said:

Homework Statement


RQwRhjc.jpg



Homework Equations


Y=1/2*(X1-X3)^2+1/14*(X2+2X4-3X5)^2


The Attempt at a Solution


For (a) part, I have only learned to find the moment-generating function of Y, but not finding the p.d.f.
Moreover, the examples I have seen only involves random variables Xi to the power 1, but not to higher power.

For (b) part, the difficulty for me is just similar to part (a).

##Z_1 = X_1 - X_3## has an ##N(0,a)## distribution, ##Z_2 = X_2+2X_4-3X_5## is ##N(0,b)##, and ##Z_1, Z_2## are independent. So ##Y## involves a weighted sum of squares of independent, mean-0 random variables.
 
Ray Vickson said:
##Z_1 = X_1 - X_3## has an ##N(0,a)## distribution, ##Z_2 = X_2+2X_4-3X_5## is ##N(0,b)##, and ##Z_1, Z_2## are independent. So ##Y## involves a weighted sum of squares of independent, mean-0 random variables.

So do you mean given the random variables are independent, the sum or difference of them will also have the same distribution of them? Also, how can a duel with the square of the random variables? Do I need to consider it with transformation of variables?
 

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