# Quantitative Analysis I

This course introduces probability theory and thus serves as a basis
for courses in statistical inference (572-574) and game theory
(575-576). We will begin with an axiomatic treatment of the standard
model of probability and develop an understanding of random variables,
distributions, and expectations/moments. The development of
conditional expectations and distributions will serve as a framework
to think about learning. We will then cover hypothesis testing and
asymptotic theory from the classical perspective as well as the
Bayesian approach to decision-theory. Connections between these
historically significant approaches will be traced out. The class will
end with introductions to regression from the perspective of
projection and optimization. If time permits we will also introduce
Maximum likelihood estimation. I precepted
this course for Adam Meirowitz in the
fall of 2012.

Course Syllabus