Course Description
The principles and theory behind statistical inference. It provides justification for many statistical procedures routinely used in practice and discusses principles and theory that can be used to develop reasonable solutions to new statistical problems.
Athena Title
STATISTICAL INFER
Prerequisite
STAT 6810
Semester Course Offered
Offered spring
Grading System
A - F (Traditional)
Course Objectives
Students successfully completing this course are expected to learn various principles of statistical inference that can help select an appropriate statistical method in pursuing good practice of statistics. This course will teach them various optimal statistical procedures that can be used in statistical problem solving. This course will prepare them for a more advanced course on statistical inference.
Topical Outline
The course will cover the following topics: sufficiency and other principles of data reduction, completeness, ancillarity of a statistic, point estimation, methods of estimation, maximum likelihood method, evaluation of estimators, uniformly minimum variance unbiased estimation, Cramer-Rao inequality, efficiency, hypothesis testing, Neyman-Pearson lemma, uniformly most powerful (UMP) tests, likelihood ratio tests, monotone likelihood ratio family and applications to UMP tests, interval estimation, coverage probabilities, and confidence sets.
Syllabus
Public CV