STATS 101C
Introduction to Statistical Models and Data Mining
Lecture and discussion. The registrar has published a final exam time.
Fall 2026: 4 lectures and 12 discussions. 1 lecture and 3 discussions are open. The oldest of these readings was 6 hours ago.
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 ALMOHALWAS, AKRAM M, across recorded terms. The course summary above includes all professors.
- A+ 138 · 20.5%
- A 209 · 31.0%
- A- 172 · 25.5%
- B+ 85 · 12.6%
- B 41 · 6.1%
- B- 11 · 1.6%
- C+ 6 · 0.9%
- C 1 · 0.1%
- C- 1 · 0.1%
- D+ 4 · 0.6%
- D 1 · 0.1%
- F 5 · 0.7%
- P 2 of 677
- NP 1 of 677
Percentages are of the 674 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 | Fall 2026 |
|---|---|---|---|---|---|---|---|
| ALMOHALWAS, AKRAM M reviews ↗ | 3.68 | 3.68 | 674 | 5 | 77% | average | Closed by the department |
| 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% | - | Open, 41 seats left |
| 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. 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 Falls
Ran in 5 of the last 5 Falls.
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 Fall 2026
You enroll in the discussion, not the lecture, so a discussion's status is the one that decides whether you get in. A lecture can read open while every discussion under it is full.
Seat counts as of : the oldest of these 16 readings. Seat readings are snapshots, not live availability. Their timestamps show when dibs last checked.
-
Lec 1 MW 9:30am-10:45amClosed by the department3.68predicted, this instructor · 674 grades
99 enrolled no history
3 discussions, none open. There is no waitlist either, so the only way in is somebody dropping the lecture.
This limit is on the class, so it applies to all 3 discussions below.
-
Lec 2 MW 12:30pm-1:45pmClosed by the department3.68predicted, this instructor · 674 grades
117 enrolled no history
3 discussions, none open. There is no waitlist either, so the only way in is somebody dropping the lecture.
This limit is on the class, so it applies to all 3 discussions below.
Every discussion, with its time and seats (3)
-
Lec 3 TR 9:30am-10:45amOpen3.46predicted, this instructor · 162 grades
41 seats left. 79 of 120 enrolled low risk
3 discussions, all open.
This limit is on the class, so it applies to all 3 discussions below.
-
Lec 4 TR 11:00am-12:15pmClosed by the department3.46predicted, this instructor · 162 grades
109 enrolled no history
3 discussions, none open. There is no waitlist either, so the only way in is somebody dropping the lecture.
This limit is on the class, so it applies to all 3 discussions below.
Final enrollment, averaged across each term's sections: between 46 and 80 a term over 5 terms, summer excluded, most recently 80 in Fall 2025. That is the shape across years, not this term, which is above.
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.
Seats over time in Fall 2026
How each lecture has filled since dibs first saw it. This course runs 4 lectures; the legend under the chart picks one.
A dot is a reading where something moved: the seat count, the status, or the waitlist.
What a flat run means, and where a line starts
Flat between dots means it did not drift, it held and then jumped, and a line starts when dibs first saw that lecture rather than reaching back before it existed. A lecture that has never moved draws a flat line across the whole window, and one with two or three readings draws a line joining them, which is too few to read a trend from.
Lec 1 · Almohalwas, A.M. · 99 enrolled
Nothing read since 1 Oct, 2 hours ago. Over about 1 month before that, freed 2 seats.
Lec 2 · Almohalwas, A.M. · 117 enrolled
Nothing read since 1 Oct, 2 hours ago. Over about 1 month before that, filled by 4.
Lec 3 · Maierhofer, T.J. · 79 of 120 enrolled
Nothing read since 1 Oct, 2 hours ago. Over about 1 month before that, filled by 2.
Lec 4 · Maierhofer, T.J. · 109 enrolled
Nothing read since 1 Oct, 2 hours ago. Over about 1 month before that, freed 4 seats.
How readings and alerts work
A reading and an hourly record are different things, and most charts here hold more of the second missing than present. dibs has taken readings of a section since long before it began keeping an hour-by-hour log of when it looked, so the empty stretches are dibs saying it was not keeping that log yet, not that it looked and found nothing. That is the age of the record and not a fault.
Seat counts show the last successful read, not live availability. Refreshes can be delayed by request limits or upstream interruptions. Watched sections receive priority, but an hourly update for every section is not guaranteed.
The registrar can change a seat count between our checks. Alerts depend on dibs detecting an opening and completing delivery; a quiet watch does not prove that no seat opened. Check the registrar before enrolling.