STATS 101C
Introduction to Statistical Models and Data Mining
Grades
3.74
Average grade awarded in STATS 101C. Not a student rating: this is what the grades were.
In the A range
81%
of the 1,500 letter grades
D, F or W
0.9%
of every letter grade awarded, plus withdrawals
Taken pass/no pass
<1%
5 of 6 students passed
The registrar's own records: 1,500 grades over 9 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 9 terms ran 3.49 to 3.98.
Historical grades for all professors, across recorded terms. The course summary above includes all professors.
- A+ 346 · 23.1%
- A 567 · 37.8%
- A- 296 · 19.7%
- B+ 145 · 9.7%
- B 83 · 5.5%
- B- 29 · 1.9%
- C+ 13 · 0.9%
- C 5 · 0.3%
- C- 3 · 0.2%
- D+ 4 · 0.3%
- D 1 · 0.1%
- D- 1 · 0.1%
- F 7 · 0.5%
- P 5 of 1,506
- NP 1 of 1,506
Percentages are of the 1,500 letter grades. Grey bars are non-letter outcomes: passes (P) and no-passes (NP).
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 | Winter 2027 |
|---|---|---|---|---|---|---|---|
| ALMOHALWAS, AKRAM M reviews ↗ | 3.68 | 3.68 | 674 | 5 | 77% | average | not teaching it |
| XU, SHIRONG reviews ↗ | 3.82 | 3.82 | 315 | 2 | 86% | very light | not teaching it |
| CHEN, MILES SATORI reviews ↗ | 3.88 | 3.89 | 273 | 4 | 94% | very light | not teaching it |
| MAIERHOFER, THOMAS JOHANNES reviews ↗ | 3.46 | 3.43 | 162 | 1 | 55% | - | not teaching it |
| ZES, DAVID ANTHONY reviews ↗ | 3.92 | 3.96 | 76 | 1 | 97% | very light | 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.
What comes first
The chain dibs can see is 1 course long before STATS 101C. Read from Fall 2026, because dibs has not read a class page for STATS 101C in Winter 2027 and a department can change what it requires. This is a floor, not a deadline: dibs has not read a class page for STATS 101A, 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.
In Winters
Has not run in Winter in the 4 Winters 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.
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. Enforced requisite: course 101A. Recommended: course 101B. Designed for juniors/seniors. Applied regression analysis, with emphasis on general linear model (e.g., multiple regression) and generalized linear model (e.g., logistic regression). Special attention to modern extensions of regression, including regression diagnostics, graphical procedures, and bootstrapping for statistical influence. P/NP or letter grading.
Sections in Winter 2027
From the people who took it
Student reviews
What taking STATS 101C 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.
Looking for more perspectives?
External reviews are separate and do not count toward the dibs rating.