The mean of a sum of variables.

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Main Question or Discussion Point

How do I prove that the mean of a random variable Z which is the sum of to other random variables X and Y is the sum of the mean of X with the mean of Y?
 

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  • #2
mathman
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Essentially the theorem is equivalent to the theorem that the integral of a sum is the sum of the integrals.
 
  • #3
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well I obviously know that the integral of the sum is the sum of the integral but I don't know how I can relate that to the situation a mentioned, can you please be more specific?
I'm trying to prove it and I'm getting a convultion integral so far...
thank you.
 
  • #4
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well I obviously know that the integral of the sum is the sum of the integral but I don't know how I can relate that to the situation a mentioned, can you please be more specific?
I'm trying to prove it and I'm getting a convultion integral so far...
thank you.
Yes that'll eventually give you a proof for the special case where the rv's are independent and have densities (involves reversing the order of integration and a change of variables).

Another approach that would work for the non-independent case is to consider separately the joint distribution and marginal distributions of X and Y.
 
  • #5
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well but I'm not being able to prove it either for dependent or independent variables, can you please show me the proof or tell me where I can find it? thank you
 
  • #6
mathman
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Two random variables.
E(X+Y)=∫∫(x+y)dF(x,y)=∫∫xdF(x,y) + ∫∫ydF(x,y).
Integrate with respect to y in the first integral and integrate with respect to x in the second integral. You will be left with E(X) + E(Y).

In the above F(x,y) is the joint distribution function.
 

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