Introduction to Statistical Inference

Catalog description

Foundational inferential methods for learning about populations from samples, including point and interval estimation, and the formulation and testing of hypotheses. Statistical theory is introduced to justify approaches, including the Central Limit Theorem, sampling distributions, and methods of finding and evaluating statistical inference procedures, including point estimation, interval estimation, Bootstrap and hypothesis testing. The course emphasizes challenges that arise when applying classical inferential methods to big data sets, partially through the use of computational and simulation techniques. Prereq: STAT 301 or MATH 380 .