When writing code in general, and when implementing modern statistical approaches specifically, you’ll find yourself doing the same thing over and over and over and over. In these cases, abstracting what you’re doing into a function and then using that function across a lot of iterations can simplify your code and make analysis much easier. Here we’ll the material necessary for functions, simulations, and resampling.

This topic is made up of the following components:

• Writing functions
• Iteration and simulation
• List columns and bootstrapping

The slack channel for this topic is here.

The code that I produced working examples in lecture is here.