Quote by Tosh5457
Isn't that only for continuous random variables (and not discrete)?
Anyway, shouldn't it be easy by convolution? I think that I'm only missing something very basic...

The y variable is just a dummy variable and you can call it whatever you want. As long as you are doing a discrete convolution for PDF's with univariate distributions (i.e. with PDF in form P(X = x) = blah) then your dummy variable will always correspond to this x or whatever other dummy variable you have chosen.