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5.0
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Search Results
| Name | Grades | Rating | |||
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Not teaching in Spring 2026 | |||||
STAT 4355 Larry Ammann | |||||
A | |||||
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| Name | Grades | Rating | |||
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Not teaching in Spring 2026 | |||||
STAT 4355 Larry Ammann | |||||
A | |||||
Grades: 196
Median GPA: A-
Mean GPA: 3.143
2.5
Professor rating
3.1
Difficulty
32
Ratings given
10%
Would take again
Applied Linear Models
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: 370
Median GPA: A-
Mean GPA: 3.254
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Grades: 196
Median GPA: A-
Mean GPA: 3.143
2.5
Professor rating
3.1
Difficulty
32
Ratings given
10%
Would take again
Applied Linear Models
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: 370
Median GPA: A-
Mean GPA: 3.254
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