EDMS646

General Linear Models I

Prerequisite: EDMS645; or an equivalent introductory statistics course. A first post-introductory inferential statistics course, with emphasis on analysis of variance procedures and designs from within the general linear modeling framework. Assignments include student analysis of education and related data; application of statistical software packages is emphasized.

Fall 2025

Yang Liu

1 review
Average rating: 5.00

Spring 2025

Jeffrey Harring

0 reviews
Average rating: N/A

Yang Liu

1 review
Average rating: 5.00

Past Semesters

Tessa Johnson

0 reviews
Average rating: N/A

Jeffrey Harring

0 reviews
Average rating: N/A

Jeffrey Harring

0 reviews
Average rating: N/A

Jeffrey Harring

0 reviews
Average rating: N/A

Shujin Zhong

0 reviews
Average rating: N/A

Gregory Hancock

0 reviews
Average rating: N/A

Shujin Zhong

0 reviews
Average rating: N/A

Jeffrey Harring

0 reviews
Average rating: N/A

Yang Liu

1 review
Average rating: 5.00

Mark Lachowicz

0 reviews
Average rating: N/A

Hong Jiao

0 reviews
Average rating: N/A

Jeffrey Patton

0 reviews
Average rating: N/A

Ji Seung Yang

0 reviews
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Tracy Sweet

0 reviews
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George Macready

0 reviews
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Include P/F semesters During the Spring 2020 and Spring 2021 semesters, students could choose to take some of their courses pass-fail mid-semester which skews grade data aggregated across multiple semesters.

Average GPA of 3.44 between 751 students*

A-: 17.84%

A: 31.56%

A+: 15.31%

B-: 5.19%

B: 8.52%

B+: 9.72%

C-: 0.27%

C: 1.07%

C+: 1.6%

D: 0.67%

D+: 0.27%

F: 0.4%

W: 4.26%

other: 3.33%

* "W"s are considered to be 0.0 quality points. "Other" grades are not factored into GPA calculation. Grade data not guaranteed to be correct.