STATS 412
Advanced Regression and Predictive Modeling
Grades
3.65
Average grade awarded in STATS 412. Not a student rating: this is what the grades were.
In the A range
72%
of the 78 letter grades
D, F or W
1.3%
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: 78 grades over 4 terms, 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, and term averages across those 4 terms ran 3.13 to 3.95.
Historical grades for all professors, across recorded terms. The course summary above includes all professors.
- A 46 · 59.0%
- A- 10 · 12.8%
- B+ 9 · 11.5%
- B 8 · 10.3%
- B- 3 · 3.8%
- C- 1 · 1.3%
- F 1 · 1.3%
Percentages are of the 78 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 | Spring 2027 |
|---|---|---|---|---|---|---|---|
| WU, GUANI reviews ↗ | 3.65 | 3.65 | 78 | 4 | 72% | very heavy | 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.
In Springs
Has not run in Spring in the 4 Springs dibs holds records for, back to Fall 2021. That is 4 years of grade records rather than the course catalog, so it says what has happened and not what the department will do next. dibs has no record of it in any quarter since Fall 2024.
From the terms dibs holds, which start in Fall 2021 and exclude summer. A department can run a course in a quarter it never has before.
From the registrar's catalog
Lecture, three hours; discussion, one hour. Limited to Master of Applied Statistics students. Often we are interested in making inferences and predictions from data, either by (1) estimating particular meaningful parameters of models or (2) finding best fitting model that we can then manipulate to produce useful outputs such as predictions or counterfactual estimates. Focus on what is done when linear models are not appropriate and may produce misleading estimates. Generalized linear model and maximum likelihood methods as essential tools all statistics students should understand. Examination of shift gears to explore regression and classification techniques that have been ubiquitous in machine learning literature in recent years, with special attention to regularization and kernelized methods. Letter grading.
Sections in Spring 2027
From the people who took it
Student reviews
What taking STATS 412 was like: the work, the teaching, and what students wish they’d known.
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