Course Description:
This is a graduate-level grounding in the theory of statistical inference.
The official course description from the Yale Bulletin reads:
``A systematic development of the mathematical theory of statistical inference covering
methods of estimation, hypothesis testing, and confidence intervals. An introduction
to statistical decision theory. Undergraduate probability at the level of STAT 541a assumed.''
A brief additional remark. Most of the course will focus on
parameter estimation, and will be organized around different notions of
optimality for estimators. We will cover unbiasedness, equivariance,
Bayes estimators, and minimax theory, as well as large sample theory
(that is, what happens when data size grows to infinity).
Course Website:
Log on to the Classes.v2 server (Yale only).