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

Enrollment Information
Syllabi: none
  •   Choose one lecture and one laboratory. Combined with: BTRY 4030STSCI 4030

  • 4 Credits Stdnt Opt

  • 13120STSCI 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.

  • 13121STSCI 5030  LAB 401

  • 13122STSCI 5030  LAB 402

  • 18314STSCI 5030  LAB 403

  • 18315STSCI 5030  LAB 404