STSCI 5030

STSCI 5030

Course information provided by the 2017-2018 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.


Prerequisites/Corequisites Prerequisite: 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, or permission of instructor.

When Offered Fall.

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

  • 4 Credits Stdnt Opt

  • 13120 STSCI 5030   LEC 001

  • Instruction Mode: In Person

    Prerequisites: 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, or permission of instructor. Intended for MPS students in Applied Statistics.

  • 13121 STSCI 5030   LAB 401

  • Instruction Mode: In Person

  • 13122 STSCI 5030   LAB 402

  • Instruction Mode: In Person

  • 18314 STSCI 5030   LAB 403

  • Instruction Mode: In Person

  • 18315 STSCI 5030   LAB 404

  • Instruction Mode: In Person