Course Number
625.661
Next Offered
Spring 2025
Location
Online
Course Format
Asynchronous Online

Introduction to regression and linear models including least squares estimation, maximum likelihood estimation, the Gauss-Markov Theorem, and the Fundamental Theorem of Least Squares. Topics include estimation, hypothesis testing, simultaneous inference, model diagnostics, transformations, multicollinearity, influence, model building, and variable selection. Advanced topics include nonlinear regression, robust regression, and generalized linear models including logistic and Poisson regression.

Course Prerequisite(s)

EN.625.603 Statistical Methods and Data Analysis, multivariate calculus, and basic knowledge of matrix and linear algebra.

Course Offerings

Open

Statistical Models and Regression

625.661.81
01/21/2025 - 05/06/2025
Semester
Spring 2025
Course Format
Asynchronous Online
Location
Online
Cost
$5,270.00
Course Materials
Open

Statistical Models and Regression

625.661.82
01/21/2025 - 05/06/2025
Semester
Spring 2025
Course Format
Asynchronous Online
Location
Online
Cost
$5,270.00
Course Materials
Waitlist Only

Statistical Models and Regression

625.661.83
01/21/2025 - 05/06/2025
Semester
Spring 2025
Course Format
Asynchronous Online
Location
Online
Cost
$5,270.00
Course Materials