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Applied Linear Models
STAT 4355
School of Natural Sciences and Mathematics
Introduction to linear statistical models and their application to empirical data. Topics include linear and logistic regression; multiple regression; diagnostic measures; detection of outliers and influential observations; variable selection; one- and two-way ANOVA; analysis of covariance; model fitting and validation using the statistical programming language R. 3 credit hours.
Prerequisite: STAT 3355 or instructor consent required.
Offering Frequency: Each year
Grades: 314
Median GPA: A-
Mean GPA: 3.288
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Applied Linear Models
STAT 4355
School of Natural Sciences and Mathematics
Introduction to linear statistical models and their application to empirical data. Topics include linear and logistic regression; multiple regression; diagnostic measures; detection of outliers and influential observations; variable selection; one- and two-way ANOVA; analysis of covariance; model fitting and validation using the statistical programming language R. 3 credit hours.
Prerequisite: STAT 3355 or instructor consent required.
Offering Frequency: Each year
Grades: 314
Median GPA: A-
Mean GPA: 3.288
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