Model Thinking, from coursera.
A funny coincidence; last week I reached the... SIS epidemiology model! Rarely so relevant.
It's quite interesting. Two of the things that fascinated me most so far are emergent properties (such as in cellular automata models), and what he calls the models' "fertility".
As an example, with a few adjustments (ie the "recovery rate" becomes a "churn rate", etc) the SIS model could be adapted in marketing, viral or not, to measure an existing campaign's efficiency, or try to predict the means a future one might require based on different assumptions and goals.
Also acted as a nice statistics 101 refresher / intro
It's quite interesting. Two of the things that fascinated me most so far are emergent properties (such as in cellular automata models), and what he calls the models' "fertility".
As an example, with a few adjustments (ie the "recovery rate" becomes a "churn rate", etc) the SIS model could be adapted in marketing, viral or not, to measure an existing campaign's efficiency, or try to predict the means a future one might require based on different assumptions and goals.
Also acted as a nice statistics 101 refresher / intro