Description:

This course covers theoretical and applied fundamentals of statistical inference. The primary topics include principles of data reduction, point estimation, hypothesis testing, interval estimation and asymptotic methods.

Prerequisite：

Understand discrete and continuous random variables, transformations and expectations, common families of distributions, multiple random variables, differential and integral calculus

Reference：

Casella and Berger. Statistical Inference Second Edition, 2002.