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The mean of a sum of variables.

by Mppl
Tags: variables
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Mppl
#1
Nov4-11, 03:38 PM
P: 13
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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mathman
#2
Nov4-11, 03:48 PM
Sci Advisor
P: 6,027
Essentially the theorem is equivalent to the theorem that the integral of a sum is the sum of the integrals.
Mppl
#3
Nov4-11, 03:54 PM
P: 13
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.

bpet
#4
Nov4-11, 09:58 PM
P: 523
The mean of a sum of variables.

Quote Quote by Mppl View Post
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.
Mppl
#5
Nov5-11, 04:06 AM
P: 13
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
mathman
#6
Nov5-11, 04:03 PM
Sci Advisor
P: 6,027
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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