Agreed. I think in light of the fact that a lot of this stuff is learned iteratively you’d want to unpack ‘basic mathematics’. I’m not sure of the best way to graphically represent iterative learning, but maybe you could have arrows going back to certain subjects, or you could have ‘statistics round II’ as one of nodes in the network.
It seems like insights are what you’re really aiming at, so maybe instead of ‘probability theory’ you have a node for ‘distributions’ and ‘variance’ at some early point in the tree then later you have ‘Bayesian v. Frequentist reasoning’.
This would help also help you unpack basic mathematics, though I don’t know much about the dependencies either. I hope too, soon :)
Agreed. I think in light of the fact that a lot of this stuff is learned iteratively you’d want to unpack ‘basic mathematics’. I’m not sure of the best way to graphically represent iterative learning, but maybe you could have arrows going back to certain subjects, or you could have ‘statistics round II’ as one of nodes in the network.
It seems like insights are what you’re really aiming at, so maybe instead of ‘probability theory’ you have a node for ‘distributions’ and ‘variance’ at some early point in the tree then later you have ‘Bayesian v. Frequentist reasoning’.
This would help also help you unpack basic mathematics, though I don’t know much about the dependencies either. I hope too, soon :)