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Search Results
| Name | Grades | Rating | |||
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Not teaching in Spring 2026 | |||||
STAT 4355 Sunyoung Shin | |||||
A- | |||||
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| Name | Grades | Rating | |||
|---|---|---|---|---|---|
Not teaching in Spring 2026 | |||||
STAT 4355 Sunyoung Shin | |||||
A- | |||||
Sunyoung Shin
[email protected]Grades: 612
Median GPA: A-
Mean GPA: 3.235
2.9
Professor rating
3.4
Difficulty
16
Ratings given
50%
Would take again
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: 370
Median GPA: A-
Mean GPA: 3.254
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Sunyoung Shin
[email protected]Grades: 612
Median GPA: A-
Mean GPA: 3.235
2.9
Professor rating
3.4
Difficulty
16
Ratings given
50%
Would take again
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: 370
Median GPA: A-
Mean GPA: 3.254
Click a checkbox to add something to compare.