Return to search
Informatics and Computing
Description: Matrix-based coverage of linear statistical models for independent data from frequentist and Bayesian perspectives, including regression, analysis of variance (ANOVA), estimation, testing, selection, diagnostics, and associated random variables and probability distributions. Letter grade only.
Units: 3
Sections offered: Spring 2026 Fall 2026
Prerequisite: Admission to Informatics and Computing PhD, Informatics and Computing MS, Computational and Applied Data Science MS, Computer Science MS, or Electrical Engineering MS
Informatics and Computing
Term : Spring 2026
Catalog Year : 2025-2026
INF 511 - Modern Regression I
Description: Matrix-based coverage of linear statistical models for independent data from frequentist and Bayesian perspectives, including regression, analysis of variance (ANOVA), estimation, testing, selection, diagnostics, and associated random variables and probability distributions. Letter grade only.
Units: 3
Sections offered: Spring 2026 Fall 2026
Prerequisite: Admission to Informatics and Computing PhD, Informatics and Computing MS, Computational and Applied Data Science MS, Computer Science MS, or Electrical Engineering MS