Graphical understanding of the convolution of discrete distributions. I am studying convolution and trying to get a visual sense of the process. From the wikipedia page I understand what 2 continuous gaussian or 2 uniform distributions will produced when convolved, but I'm having a hard time determine what discrete distributions will look like when convolved. What does the convolution of various discrete distributions look like graphically? Specifically, I'm trying to understand what the histograms of 2 discrete normal and uniform distributions would look like when convolve. Thanks in advance for the help.

It will change almost nothing. You will get the same picture that you got for the continuous case. The idea is the same (shift, multiply,+sum). In the discrete case you have summation instead of integrals. The area under a curve is in the discrete case just the summation of the multiplication of some numbers. Simply same story.