ECON 570 introduces the data underlying quantitative economic analysis, teaching students to formulate research questions, access data sources, conduct analysis, and report findings professionally.
John Brauer's course involves significant Python coding for econometrics, which reviewers find difficult without prior CS or econometrics background, though one Data Science student found it easy.
All recorded terms · compare terms & instructors
[ECON 310, (STAT 240 and 340), or (STAT 303 and 333)], and (ECON 301 or 311)
This is a best-effort interpretation; check the catalog requirements above.
Ashley Swanson delivers impeccable, interesting, and informative lectures that cover many topics quickly but not deeply. Reviewers describe her as friendly and the class as straightforward with low time consumption, though she is noted as a tough grader despite heavy curving.
Recent recorded grades — Spring 2024: 3.77 GPA, 88.5% A/AB (n=96 letter grades); Fall 2024: 3.80 GPA, 92.1% A/AB (n=89 letter grades); Fall 2025: 3.79 GPA, 91.5% A/AB (n=82 letter grades).
John Brauer teaches ECON 570 with a heavy emphasis on coding econometrics in Python, though one reviewer notes he explains little code and the course is mislabeled regarding prerequisites.
Other students found the course easy with low stress and good content, while another reviewer described Brauer as fair and understanding for those who attend class.
Recent recorded grades — Spring 2025: 3.81 GPA, 92.2% A/AB (n=129 letter grades); Fall 2025: 3.82 GPA, 94.6% A/AB (n=74 letter grades); Spring 2026: 3.79 GPA, 91.1% A/AB (n=157 letter grades).
No course-specific feedback yet.
No course-specific feedback yet.
Historical reviews for Kim Ruhl describe him as caring, accessible, and clear, with students valuing his supportive feedback and project-based learning. Conversely, recent reviews criticize his lectures as unengaging and report inconsistent grading standards, including a dispute over an F grade for a well-researched paper versus an A+ for a simple suggestion.
ASHLEY SWANSON is recorded teaching in Spring 2023, Spring 2024, Fall 2024, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.
JOHN BRAUER is recorded teaching in Spring 2025, Fall 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.
KIM RUHL is recorded teaching in Spring 2020, Spring 2022, Fall 2023. Recorded history may be incomplete and does not establish a future schedule.
Recorded history may be incomplete and does not establish a future schedule.
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| Section | Mode | Enrolled / capacity | Waitlist |
|---|---|---|---|
| LEC 001 | Classroom Instruction | 94 / 96 | 9 |
| DIS 301 | Classroom Instruction | 24 / 24 | 1 |
| DIS 302 | Classroom Instruction | 23 / 24 | 5 |
| DIS 303 | Classroom Instruction | 24 / 24 | 3 |
| DIS 304 | Classroom Instruction | 23 / 24 | 0 |
| LEC 002 | Classroom Instruction | 96 / 96 | 2 |
| DIS 311 | Classroom Instruction | 24 / 24 | 0 |
| DIS 312 | Classroom Instruction | 24 / 24 | 2 |
| DIS 313 | Classroom Instruction | 24 / 24 | 0 |
| DIS 314 | Classroom Instruction | 24 / 24 | 0 |
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.
Students report mixed experiences with current instructors Ashley Swanson and John Brauer. Swanson offers clear, fast-paced lectures with tough grading, while Brauer provides valuable Python content and is viewed as fair and understanding.
Recent recorded grades — Spring 2025: 3.81 GPA, 92.2% A/AB (n=129 letter grades); Fall 2025: 3.80 GPA, 92.9% A/AB (n=156 letter grades); Spring 2026: 3.79 GPA, 91.1% A/AB (n=157 letter grades).
John Brauer's course involves significant Python coding for econometrics, which reviewers find difficult without prior CS or econometrics background, though one Data Science student found it easy.
Ashley Swanson is praised for impeccable, interesting lectures and fairness despite tough grading. John Brauer is viewed as fair and understanding, with students noting that attending class and paying attention leads to an enjoyable experience.
Latest available · Spring 2026— not enough history to project Fall 2026.
Through Spring 2026
Latest available grades · Spring 2026 · all course levels
GPA
Higher than % of other courses in this group.
Course GPAs · red marks this course’s range
letter grades
More recorded grades than % of other courses in this group.
Typical course in this group: letter grades.
1283 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.
Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.
Descriptions, prerequisites, and recorded course offerings.
Observations at scan time; dates do not imply when a catalog change took effect.
Fundamentals of Data Analytics for Economists
Recorded 2026-09-07[
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"term_id": "1272",
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"title": "Fundamentals of Data Analytics for Economists",
"credits_min": 3,
"credits_max": 4,
"typically_offered": "Not Applicable"
}
]Original comments behind the course and instructor summaries.
Recorded grade distributions by term, section, and instructor.
Explore recorded gradesRecorded model configuration, reasoning, and tool conversations.
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