PUB PLC C277
Network Science Using R
Grades
3.56
Average grade awarded in PUB PLC C277. Not a student rating: this is what the grades were.
In the A range
67%
of the 12 letter grades
D, F or W
0.0%
of every letter grade awarded, plus withdrawals
Taken pass/no pass
-
the registrar has this letter grade only this term
The registrar's own records: 12 grades over 1 term, Fall 2021 to Fall 2025. Every instructor is pooled here.
What is inside that record
No summer session is in that record.
The table below splits them.
Historical grades for all professors, across recorded terms. The course summary above includes all professors.
- A+ 1 · 8.3%
- A 4 · 33.3%
- A- 3 · 25.0%
- B+ 2 · 16.7%
- B 1 · 8.3%
- C 1 · 8.3%
Percentages are of the 12 letter grades. Grey bars are non-letter outcomes.
How the non-letter outcomes are counted
They are excluded from the GPA entirely rather than scored, because counting a P as a 4.0 would be a fabrication.
By instructor
| Instructor | Predicted GPA | Raw | n | Terms | A range | Workload | Summer Session A 2026 |
|---|---|---|---|---|---|---|---|
| STEINERT-THRELKELD, ZACHARY reviews ↗ | 3.60 | 3.56 | 12 · | 1 | 67% | - | not teaching it |
Why Predicted is not the Raw average
“Predicted” is shrunk toward the course average, which is itself shrunk toward the department, so an instructor with a handful of students sits near the course mean rather than topping the list.
Grade records describe outcomes. For what a course is like to take, read student reviews written on dibs below or follow the separate external review link.
Workload and assignments
Work types reported in BruinWalk reviews of this course, across recorded instructors and terms. They may differ from this term's syllabus.
dibs has not read this course’s reviews, so it cannot say what kind of work it sets. That is dibs not having looked. It is not a course without papers or exams, and the reviews linked below are the answer until dibs catches up.
From the registrar's catalog
Lecture, three hours. No prior knowledge of R required. Designed for graduate students. Network analysis offers framework for understanding how relationships between people, places, and institutions affect public policy outcomes. For example, why individuals decide to protest or vote, amount of education they pursue, or effect of human interference in ecosystem can all be considered using network analysis. Weekly introduction of concept from network analysis, followed by working through it using popular statistical programming language R. Concurrently scheduled with course CM177. Letter grading.
Sections in Summer Session A 2026
From the people who took it
Student reviews
What taking PUB PLC C277 was like: the work, the teaching, and what students wish they’d known.
Your experience could be the first.
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