This talk gives a glimpse of some of the methods and math that allow us to understand feedback systems. Continuing on from Part 1, it gives a description of how we use scientific principles to derive models of the behavior we wish to understand.  Those models often take the form of differential equations, and to simplify our understanding, we use transform theory to convert the equations into a mostly equivalent, but simpler to manage set of equations that rely on algebra.  (The viewer need not understand differential equations or transform theory to understand this unit. They referred to so that the audience does not think we are just making stuff up.) Once we get to the algebra, we can get a lot of intuition about how our system is behaving and insights into how to make adjustments to make it behave better. 

This last part is why engineers learn math to begin with.  Not just to model what we observe, but to help us predict how to adjust things to make it better.