This is just the setting of the example. For each of those distributions he takes two of them which don't overlap much and looks at the convolution (i.e. the di

This is just the setting of the example. For each of those distributions he takes two of them which don't overlap much and looks at the convolution (i.e. the distribution of the sum of two independent random variables described by them). Edit: by the way, the irony is that the convolution calculates products of probabilities and adds them!