Convolution theorem - Sum of random variable and constant

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Problem:

Random variables X, Y are independent. X has normal distribution with parameters (a= 1, b^2 = 4). Y has also normal distribution, but Y is equal to (-X). Find all constants c and k > 0,in order to find X + Y + c and k*X so they would have same distribution.

I found out, it has to be done throught convolution theorem. So first I will sum two random variables and then compute constant c. But I don't really know how to compute the constant. My idea is to use definite integral of f(z) + c = 1 (f(z) is X+Y). Is it correct?

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Please see solution in the image. You don't need to perform convolution as The sum of Gaussian RV's is also Gaussian.

solution