ECON 434
Machine Learning and Big Data for Economists
Course statistics
- Predicted GPA
- 3.72
- n = 193 · 4 terms · ± 0.038
- A range
- 79%
- of letter grades
- Taken P/NP
- 0%
- — of those passed
- D / F / W
- 0.0%
- incl. withdrawals
Sections in Fall 2026
Not offered in Fall 2026.
Enrollment history
Final enrollment per term, averaged across that term's sections. Four years deep, summer excluded. Per-section live curves are on each section page.
- 3922S
- 2023S
- 6624S
- 6825S
Peak 68
Most recent
68
in 25S
4 terms on record
Grade distribution
- A+ 40 · 20.7%
- A 88 · 45.6%
- A- 24 · 12.4%
- B+ 17 · 8.8%
- B 10 · 5.2%
- B- 10 · 5.2%
- C+ 4 · 2.1%
Grey bars are non-letter outcomes — P/NP, S/U, incompletes. 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 | Raw | n | Terms | A range |
|---|---|---|---|---|---|
| CHETVERIKOV, DENIS NIKOLAYEVICH | 3.75 | 3.75 | 193 | 4 | 79% |
“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.
By term
- 22S 3.92 n=39
- 23S 3.96 n=20
- 24S 3.92 n=66
- 25S 3.42 n=68