STSCI 4030

Linear Models with Matrices

Course Description

Course information provided by the Courses of Study 2022-2023.

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.

When Offered Fall.

Prerequisites/Corequisites Prerequisite: STSCI 2150 or STSCI 2200/BTRY 3010 or equivalent, BTRY 3080 or equivalent, MATH 1920 or MATH 2130 or equivalent, MATH 2210 or equivalent, STSCI 3200/BTRY 3020 or BTRY 6020.

Distribution Category (SDS-AS)

• 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.

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