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

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Homework Help Overview

The discussion revolves around calculating the expected value E(XY) for two random variables X and Y that are not independent, given a joint probability density function (pdf) f_{XY}(x,y) = (2+x+y)/8 defined over the range -1

Discussion Character

  • Exploratory, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • Participants discuss the necessity of integration to find E(XY) and question the applicability of the formula E(XY) = E(X)E(Y) when X and Y are not independent. There is a mention of using the definition of expectation for joint distributions.

Discussion Status

The conversation is ongoing, with some participants emphasizing the need for integration to find the expected value, while others express frustration over the lack of a textbook or clear guidance. There are differing opinions on the symmetry of the function and its implications for E(XY).

Contextual Notes

Participants note the absence of a textbook and the challenge of understanding the material without adequate resources. There is also a mention of the original poster's previous calculations regarding the independence of X and Y.

laura_a
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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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