STATS 100C
Linear Models
Grades
3.48
Average grade awarded in STATS 100C. Not a student rating: this is what the grades were.
In the A range
53%
of the 1,248 letter grades
D, F or W
0.6%
of every letter grade awarded, plus withdrawals
Taken pass/no pass
<1%
5 of 5 students passed
The registrar's own records: 1,248 grades over 14 terms, Fall 2021 to Fall 2025. Every instructor is pooled here.
What is inside that record
4 of those terms are summer sessions, and summer sessions are counted here.
The table below splits them, and term averages across those 14 terms ran 3.00 to 3.79.
Historical grades for all professors, across recorded terms. The course summary above includes all professors.
- A+ 56 · 4.5%
- A 340 · 27.2%
- A- 270 · 21.6%
- B+ 303 · 24.3%
- B 166 · 13.3%
- B- 49 · 3.9%
- C+ 32 · 2.6%
- C 19 · 1.5%
- C- 6 · 0.5%
- D+ 3 · 0.2%
- F 4 · 0.3%
- P 5 of 1,261
- I 8 of 1,261
Percentages are of the 1,248 letter grades. Grey bars are non-letter outcomes: passes (P) and incompletes (I).
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 |
|---|---|---|---|---|---|---|---|
| CHRISTOU, NICOLAS reviews ↗ | 3.50 | 3.50 | 689 | 11 | 50% | heavy | not teaching it |
| MADRID PADILLA, OSCAR HERNAN reviews ↗ | 3.23 | 3.20 | 154 | 3 | 38% | - | not teaching it |
| LEONG, OSCAR reviews ↗ | 3.34 | 3.32 | 153 | 2 | 43% | - | not teaching it |
| TSIANG, MICHAEL reviews ↗ | 3.78 | 3.81 | 141 | 2 | 86% | light | not teaching it |
| AMINI, ARASH ALI reviews ↗ | 3.48 | 3.49 | 111 | 2 | 66% | average | 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.
What the work looks like
- Exams mentioned, no number given, said by 13 reviewers
- Quizzes mentioned, no number given, said by 1 reviewer
- Problem sets mentioned, no number given, said by 9 reviewers
Read from 60 reviews 26 days ago. dibs counts only what a review actually states, so a kind of work nobody mentioned is absent rather than zero.
What comes first
The chain dibs can see is 6 courses long before STATS 100C. Read from Fall 2026, because dibs has not read a class page for STATS 100C in Summer Session A 2026 and a department can change what it requires. This is a floor, not a deadline: dibs has not read a class page for MATH 170A and MATH 3B, so the real chain can only be longer than this, never shorter.
Counted in courses rather than quarters: dibs does not know which of them a department lets you take together.
From the registrar's catalog
Lecture, three hours; discussion, one hour. Enforced requisite: course 100B or Mathematics 170S. Theory of linear models, with emphasis on matrix approach to linear regression. Topics include model fitting, extra sums of squares principle, testing general linear hypothesis in regression, inference procedures, Gauss/Markov theorem, examination of residuals, principle component regression, stepwise procedures. P/NP or letter grading.
Sections in Summer Session A 2026
From the people who took it
Student reviews
What taking STATS 100C was like: the work, the teaching, and what students wish they’d known.
Your experience could be the first.
No student reviews are available to read on dibs for this course yet. Took it? Tell the next person what helped, what was hard, and how you spent your time.
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External reviews are separate and do not count toward the dibs rating.