STSCI 5030
Last Updated
- Schedule of Classes - January 31, 2019 7:14PM EST
- Course Catalog - January 31, 2019 7:15PM EST
Classes
STSCI 5030
Course Description
Course information provided by the Courses of Study 2018-2019.
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.
Comments Co-meets with BTRY 4030/STSCI 4030.
Regular Academic Session. Choose one lecture and one laboratory. Combined with: BTRY 4030, ILRST 7170, ORIE 7170, STSCI 4030, STSCI 7170
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Credits and Grading Basis
4 Credits Stdnt Opt(Letter or S/U grades)
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Class Number & Section Details
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Meeting Pattern
- MW Phillips Hall 101
Instructors
Hooker, G
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Additional Information
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.
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Class Number & Section Details
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Meeting Pattern
- M Mann Library B30A
Instructors
Hooker, G
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Class Number & Section Details
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Meeting Pattern
- W Mann Library B30A
Instructors
Hooker, G
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Class Number & Section Details
-
Meeting Pattern
- W Mann Library B30A
Instructors
Hooker, G
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Class Number & Section Details
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Meeting Pattern
- R Mann Library B30A
Instructors
Hooker, G
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