15 - 2 - Sources of Randomness


"If I'm writing a model of people, I don't wanna say, I know what these people are gonna do. Instead, I might say, well, you know, they're probably gonna do this, but who knows. You know, they're people. They're crazy. They might do anything. So we put in a little bit of an error term, All sorts of reasons why things may not go as we expect. There can be noise, there can be error, there can be capriciousness, there can be uncertainty, there can be complexity in the underlying process. So when we think about these models, these random models that we're gonna study, there's all sorts of things that can come into play to make the outcome not be what we expect, but to include little error term." - Transcript from Scott Page Coursera

Resource Datasbase

Scott Page Model Thinking MOOC Course