The second part of this week's work introduces two of the core ideas in the course:
- With data, we can produce conditional statements that are very good summaries of an underlying joint distribution function.
- We can require that our conditional statements have a relatively simple form—linearity in the inputs—and show that in some cases these very simple functions can still serve as a very good summary of the underlying joint distribution function