Deriving Expectations from Formulas: (y1,y2) Distribution

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The discussion centers on deriving expectations from the joint distribution of discrete random variables (y1, y2) with specified probabilities. The participants confirm that E{y1^2*y2^2} equals 0 due to the nature of the values, while E{y1^2}*E{y2^2} equals 1/4, derived from the probabilities of the outcomes (0,1), (0,-1), (1,0), and (-1,0). The expectation of the product of squares is zero because y1^2*y2^2 is always zero for the given pairs, while the individual expectations yield a non-zero product. This clarification resolves the initial confusion regarding the derivation of these expectations.

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electronic engineer
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Hello,
we have the following example:

Assume that (y1,y2) are discrete valued and follow such a distribution that the pair are with probability 1/4 equal to any of the following cases: (0,1),(0,-1),(1,0),(-1,0) .


E{y1^2*y2^2}=0
E{y1^2}*E{y2^2}=1/4
I don't understand how the expectations were derived . Could anyone help?

Thanks in advanced!
 
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Hello electronic engineer! :smile:

(try using the X2 and X2 icons just above the Reply box :wink:)
electronic engineer said:
E{y1^2*y2^2}=0
E{y1^2}*E{y2^2}=1/4

easy! … y12y22 is always 0, isn't it, so its expectation must be 0

and y12 is 0 0 1 and 1 with probability 0.25 each, so its expectation is 0.5 :wink:
 
I know but I thought this is only an informal answer :)
 
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