Fall 2026

Data Analytics for Economists

ECON 770 teaches quantitative economic research using core datasets and econometric modeling.

offering recorded3 credits
Recorded instructors · Fall 2026 Ashley Swanson3.7/5Alice Wu

Summary

1 / 6

Historical reviews of Kim Ruhl: The course provides hands-on experience with Python, helping students learn programming from scratch.

Grade history

average GPA
letter grades
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All recorded terms · compare terms & instructors

Prerequisites

Course map

Graduate/professional standing

  • Graduate/professional standing
ECON 770

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree
  • Graduate/professional standing

Professors

Fall 2026
/5Adjusted rating
/5RMP difficulty
captured reviews
About this rating

Raw average: 4.50/5 from 2 quality ratings. The adjusted rating blends this with the UW review average (3.66/5), weighted as 20 additional ratings. Smaller samples stay closer to that average. Each captured review is counted once in the prior; this does not correct who chooses to leave a review.

RMP profile ↗ · All captured review dates; profile matched by name.

Recent recorded grades — Fall 2023: 3.74 GPA, 96.0% A/AB (n=75 letter grades); Fall 2024: 3.77 GPA, 94.8% A/AB (n=58 letter grades); Fall 2025: 3.77 GPA, 94.2% A/AB (n=52 letter grades). Includes jointly taught sections.

Recent recorded grades — Fall 2025: 3.77 GPA, 94.2% A/AB (n=52 letter grades). Includes jointly taught sections.

Historical instructors & teaching patterns

Historical reviews for Kim Ruhl describe well-organized lectures that teach Python from scratch and provide hands-on data analysis experience. No current instructor reviews are available to assess Alice Wu or Ashley Swanson.

ALICE WU is recorded teaching in Fall 2025. Recorded history may be incomplete and does not establish a future schedule.

ASHLEY SWANSON is recorded teaching in Fall 2023, Fall 2024, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.

KIM RUHL is recorded teaching in Fall 2020, Fall 2021, Fall 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.

Calendar & sections

Fall 2026

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction37 / 500

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records

Student experience

the class

Kim Ruhl's historical version of ECON 770 offers a well-organized, inspirational introduction to Python for data analysis and visualization, suitable for beginners.

Recent recorded grades — Fall 2023: 3.74 GPA, 96.0% A/AB (n=75 letter grades); Fall 2024: 3.77 GPA, 94.8% A/AB (n=58 letter grades); Fall 2025: 3.77 GPA, 94.2% A/AB (n=52 letter grades).

difficulty & workload

Historical reviews of Kim Ruhl: The course provides hands-on experience with Python, helping students learn programming from scratch.

Historical reviews of Kim Ruhl: Reviewers found the lectures well-organized and inspiring, noting the class effectively teaches data analysis and visualization skills to those with no prior programming background.

Topics

  • Core economic datasets
  • Econometric models

Skills

  • Clean and manipulate economic datasets
  • Implement econometric models

Grades

Latest available · Fall 2025— not enough history to project Fall 2026.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Fall 2025

More grade details Grade mix, volume & source data

Where this course fits relative to

Latest available grades · Fall 2025 · 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.

About this comparison

1320 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.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

Selected offering source records
ECON 770 · Fall 2026

Data Analytics for Economists

Recorded 2026-09-07
Raw records
[
  {
    "run_id": "20260907T155543-ce3781c4",
    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "offering_id": "1272:296:025532",
    "course_id": "ECON 770",
    "course_uid": "course_7657616b432ed8fee5f3bdf3",
    "term_id": "1272",
    "source_course_id": "025532",
    "source_subject_id": "296",
    "title": "Data Analytics for Economists",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Not Applicable"
  }
]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Model & dataset provenance
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "40ea167e457af14eef0bae1f188f3800013f9327c747a60688073d027c029ca6",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}