STSCI 5030

STSCI 5030

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: 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.

View Enrollment Information

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

  • 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

  • 13122 STSCI 5030   LAB 402

  • 18314 STSCI 5030   LAB 403

  • 18315 STSCI 5030   LAB 404