MATH 5500 - Regression I

This is an applied linear regression course that will initially focus on strengthening the student’s undergraduate background in statistics. Topics for this section will include: sampling distributions, point estimates, confidence intervals, hypothesis testing, ANOVA, and sample size calculations. The second part of the course will introduce maximum likelihood estimation and topics in linear and non-linear regression. The course will blend hands-on data analysis and a theoretical framework.

Credits: 3

Prereq: Undergraduate Statistics. Acceptance into the Masters in Mathematical Sciences program and/or instructor permission.
Lecture hours: 3
Course/lab fee: $