MATH 533 — Regression and Analysis of Variance

Name: MATH 533 — Regression and Analysis of Variance
Rating: 1.0 (19 reviews)

Multivariate normal and chi-squared distributions; quadratic forms. Multiple linear regression estimators and their properties. General linear hypothesis tests. Prediction and confidence intervals. Asymptotic properties of least squares estimators. Weighted least squares. Variable selection and regularization. Selected advanced topics in regression. Applications to experimental and observational data.

Rating: 1.00 out of 5 from 19 student reviews
Difficulty: 4.00 out of 5
Credits: 4
Faculty: Faculty of Science
Department: Mathematics and Statistics
Taught by: Abbas Khalili
Prerequisites: MATH 357, MATH 247 or MATH 251.

Sections offered

Section 001 (Lec), Wed Fri 1:05-2:25 pm — 22 seats open