Course Description
Builds the foundation in probability distribution theory that is necessary to learn statistical inference. Emphasizes mathematical rigor and includes topics such as probability laws; random variables and probability distributions; joint, marginal and conditional distributions; expectation and conditional expectation; transformations; and properties of a random sample.
Athena Title
PROBABILITY DIST
Prerequisite
STAT 4520/6520 or permission of department
Semester Course Offered
Offered fall
Grading System
A - F (Traditional)
Course Objectives
Students successfully completing this course are expected to have mastery over probability distribution theory. This course will prepare students for a rigorous course on statistical inference.
Topical Outline
The course will cover the following topics: basic probability, transformations and expectations, common families of distributions, multiple random variables, and properties of a random sample.
Syllabus