Convolute and geometrical probability spaces

Let X and Y be two independent random variables, either discrete or continuous. The question is "what is the probability distribution of Z = X + Y"? Clearly, the probability distribution of Z = X + Y is some combination of fX and fY which is called the convolution of fX and fY. It is denoted by ∗. We have fZ(t) = fX+Y(t) = fX(t)∗fY(t). In this paper it is shown how we can use geometrical probability spaces to find (without convolution) the distribution of random variable Z = X + Y.