STSCI 4030

Last Updated

  • Schedule of Classes - January 7, 2018 7:14PM EST
  • Course Catalog - January 7, 2018 7:15PM EST

STSCI 4030
Linear Models with Matrices

Course information provided by the Courses of Study 2017-2018.

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: A two-semester sequence on statistical methods (e.g. BTRY 3010-BTRY 3020), a course on probability and distribution theory (e.g. BTRY 3080 or MATH 4710), multivariable calculus, and linear/matrix algebra.

Outcomes
  • 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:

  •   Regular Academic Session.  Choose one lecture and one laboratory. Combined with: BTRY 4030, STSCI 5030

  • 4 Credits Stdnt Opt

  • 11884 STSCI 4030   LEC 001

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  • A two-semester sequence on statistical methods (e.g. BTRY 3010-BTRY 3020), a course on probability and distribution theory (e.g. BTRY 3080 or Math 4710), multivariable calculus, and linear/matrix algebra.

  • 12395 STSCI 4030   LAB 401

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  • 12637 STSCI 4030   LAB 402

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  • 18310 STSCI 4030   LAB 403

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  • 18311 STSCI 4030   LAB 404

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