The MGF of the sum of independent random variables is the product of the MGFs of the random variables. You should be able to show this pretty easily using the definition of independence and the definition of the MGF.
How do i show that the a [X1 has a chi square distribution with n degrees of freedom] + [X2 has a chi square distribution with m degrees of freedom] is a [X1+X2 has a chi square distribution with n+m degrees of freedom]?
How can i use moment generating functions to do this?
The MGF of the sum of independent random variables is the product of the MGFs of the random variables. You should be able to show this pretty easily using the definition of independence and the definition of the MGF.
the mgf for a chi square with n freedoms is
(1-2t)^(-n/2)
the mgf for a chi square with m freedoms is
(1-2t)^(-m/2)
The MGF of the sum of independent random variables is the product of the MGFs of the random variables. So the product is
(1-2t)^(-(n+m)/2)
which is a chi squared distribution with n+m degrees of freedom
so in conclusion [X1 has a chi square distribution with n degrees of freedom] + [X2 has a chi square distribution with m degrees of freedom] is a [X1+X2 has a chi square distribution with n+m degrees of freedom]
Is this right?
Looks fine to me. But it'll only pass as a proof for a class if you've proved or at least have been shown that fact about MGFs that I mentioned before. Otherwise you'll have to derive that result yourself.
Looks good to me.
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