Making probabilistic estimates involves different kinds of distributions over variables, then sometimes combining those distributions, doing sensitivity analysis, visualising your new distribution, and so on. The thought is that itās very clumsy to do this with e.g. Python plus a bunch of data viz libraries.
Note there is Squigglepy, which was announced here by Peter Wildeford. It āimplements many Squiggle-like functionalities in Pythonā.
On the billionaire impact list, there is this proposal from Elliot Olds (and this shallow analysis of the top 10 richest people from NuƱo Sempere, and this very shallow one from me).
On the forecasting guide, there is this great hands-on online course. The lead instructor is Jacob Steinhardt.
Great ideas, Fin!
On the BOTEC tools, regarding:
Note there is Squigglepy, which was announced here by Peter Wildeford. It āimplements many Squiggle-like functionalities in Pythonā.
On the billionaire impact list, there is this proposal from Elliot Olds (and this shallow analysis of the top 10 richest people from NuƱo Sempere, and this very shallow one from me).
On the forecasting guide, there is this great hands-on online course. The lead instructor is Jacob Steinhardt.