What Is a Graphical Model?

A graphical model is a problistic model on a network. We don't get to observe edges, but we actually get to observe data on the no. So as an example, m and since you know m here, we'll also care about biological applications. And so we would like to learn a this network among these genes. Now, what does this have to do with causality? I mean, isn't causality something you can only get at by randomization? Or is there another way to infer causal structures? Yes, this is really interesting. There has been a very long debate in statistics wo actually figure these things out.