How to find E(XY) when X and Y are NOT indepdant?

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To find E(XY) when X and Y are not independent, integrate the product xy against the joint probability density function f_{XY}(x,y). The formula is E(XY) = ∫∫ xy f(x,y) dy dx over the specified limits. Independence is not required for this calculation, and the expectation cannot be simplified using E(X) and E(Y) alone. The joint pdf provided is f_{XY}(x,y) = (2+x+y)/8 for -1
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Homework Statement



I have a joint pdf f_{XY}(x,y) = (2+x+y)/8 for -1<x<1 and -1<y<1

Homework Equations



I have to work out E(XY) but I have previously worked out that X and Y are NOT independent (that is f_{XY}(0,1) doesn't equal f_X{0}*f_Y{1}). I am using maxima so I don't need help with any integration, I just need to know what formula because I've read that E(XY) = E(X)E(Y) only when they're indepdant... so what happens when they're not?
 
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You integrate xy against the pdf. Do you not have the textbook?
 
No, there is no textbook for this, I have bought some books, but none of them are written for people who aren't the best at statistics. I have no idea what you mean, isn't there an easier way using E(X) and E(Y) which I already have?
 
No, there's not. Is this for a class?
 
Oh goody double posting! Laura you now have two people telling you the same thing-- integrate. I don't know why you had to start two threads on the same topic instead of just being patient.
 
You can use the definition of an expectation.
E(XY) = \oint\ointx*y*f(x,y) dy dx
Or you could argue that since the function is symmetric about 0 and the intervals [-1, 1] are centred about 0 that E(XY) = 0
 
The density isn't symmetric about zero.

Laura, for any joint continuous distribution, whether or not X, Y are independent, you can find E[XY] as

<br /> \iint xy f(x,y) \, dxdy<br />
 

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