BTRY 4030

BTRY 4030

Course information provided by the 2025-2026 Catalog.

The focus of this course is the theory and application of the general linear model expressed in its matrix form. Topics will include: least squares estimation, multiple linear regression, coding for categorical predictors, residual diagnostics, anova decomposition, polynomial regression, model selection techniques, random effects and mixed models, maximum likelihood estimation and distributional theory assuming normal errors. Homework assignments will involve computation using the R statistical package.


Distribution Requirements (DLS-AG, OPHLS-AG), (SDS-AS), (STA-IL)

Last 3 terms offered 2024FA, 2023FA, 2022FA

Learning Outcomes REF-FA25

  • Students will be able to discuss the mathematical foundations of linear statistical models using matrix algebra.
  • Students will be able to use diagnostic measures to assess the validity of a given statistical model.
  • Students will be able to analyze data involving both fixed and random factors.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one laboratory. Combined with: STSCI 4030STSCI 5030

  • 4 Credits Stdnt Opt

  •  1292 BTRY 4030   LEC 001

    • MW
    • Aug 25 - Dec 8, 2025
    • Kowal, D

  • Instruction Mode: In Person

  •  1317 BTRY 4030   LAB 401

    • M
    • Aug 25 - Dec 8, 2025
    • Kowal, D

  • Instruction Mode: In Person

  •  1329 BTRY 4030   LAB 402

    • W
    • Aug 25 - Dec 8, 2025
    • Kowal, D

  • Instruction Mode: In Person

  •  1386 BTRY 4030   LAB 403

    • W
    • Aug 25 - Dec 8, 2025
    • Kowal, D

  • Instruction Mode: In Person

  •  1387 BTRY 4030   LAB 404

    • R
    • Aug 25 - Dec 8, 2025
    • Kowal, D

  • Instruction Mode: In Person