Spring 2027

Topics in Economic Data Analysis

Advanced topics in using data to answer economic questions, focusing on interpreting empirical papers and applying econometric methods to real data.

offering recorded3–4 credits
Recorded instructors · Spring 2027 Matt Friedman4.2/5Harold ChiangKaram Kang

Summary

1 / 6

Past student reviews · Matthew Friedman

Exams were described as brutal and stressful, particularly when coding independently, though the curve was considered fair.

What you’ll be able to do

  • interpret, evaluate and critique empirical economic papers

  • use specific economic or econometric methodologies to analyze real data

Source: UW Guide

Grade history

↗
average GPA
letter grades
A
AB
B
BC
C
D
F

All recorded terms · compare terms & instructors

Prerequisites

Course map

ECON 310, (STAT 240 and 340), or (STAT 303 and 333)

ECON 695

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

Prerequisite text tree

Professors

Spring 2027

Matt Friedman

Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 4.74/5 from 23 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 — Spring 2024: 3.44 GPA, 65.1% A/AB (n=43 letter grades); Fall 2024: 3.31 GPA, 54.8% A/AB (n=42 letter grades); Spring 2026: 3.16 GPA, 57.5% A/AB (n=40 letter grades).

Recent recorded grades — Spring 2023: 3.76 GPA, 86.7% A/AB (n=45 letter grades); Spring 2025: 3.75 GPA, 82.5% A/AB (n=40 letter grades); Spring 2026: 3.84 GPA, 95.1% A/AB (n=41 letter grades).

Recent recorded grades — Spring 2024: 3.80 GPA, 90.9% A/AB (n=44 letter grades); Spring 2025: 3.70 GPA, 77.3% A/AB (n=44 letter grades); Spring 2026: 4.00 GPA, 100.0% A/AB (n=38 letter grades).

Historical instructors & teaching patterns

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

HAROLD CHIANG is recorded teaching in Spring 2022, Spring 2023, Spring 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

KARAM KANG is recorded teaching in Spring 2024, Spring 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

MATTHEW FRIEDMAN is recorded teaching in Fall 2021, Spring 2023, Fall 2023, Spring 2024, Fall 2024, Spring 2026. 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

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 450
LEC 002Classroom Instruction0 / 450
LEC 003Classroom Instruction0 / 450

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

Meeting source records
Download part 1

Student experience

the class

Past student reviews · Austin Miller, Matthew Friedman

Austin Miller’s lecture slides were well-organized and helpful for problem sets, while assignments were relevant for data analysis or financial modeling.

Recent recorded grades — Spring 2025: 3.73 GPA, 79.8% A/AB (n=84 letter grades); Fall 2025: 3.84 GPA, 91.9% A/AB (n=62 letter grades); Spring 2026: 3.66 GPA, 84.0% A/AB (n=119 letter grades).

difficulty & workload

Past student reviews · Matthew Friedman

Exams were described as brutal and stressful, particularly when coding independently, though the curve was considered fair.

Past student reviews · Matthew Friedman

Matthew Friedman was happy to help students at any time, and students found the coding skills learned useful for their jobs and portfolio interviews.

Topics

  • Advanced topics in economic data analysis
  • Empirical economic papers
  • Economic and econometric methodologies

Skills

  • Interpret, evaluate, and critique empirical economic papers
  • Use economic or econometric methodologies to analyze real data

Grades

Latest available · Spring 2026— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Spring 2026

More grade details Grade mix, volume & source data

Where this course fits relative to

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.

About this comparison

1280 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.

Download part 1
Selected offering source records
ECON 695 · Spring 2027

Topics in Economic Data Analysis

Recorded 2026-10-14
ECON 695 · Spring 2027

Data Analysis and Big Data

Recorded 2026-10-14
ECON 695 · Spring 2027

Empirical Methods in Microecon

Recorded 2026-10-14
ECON 695 · Spring 2027

Metrics: AI & Machine Learning

Recorded 2026-10-14
Raw records 
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Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
Download part 1
Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1Download part 2
Model & dataset provenance 
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  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "4fad371443c80ef9f2063c7c4692c5ab0d5215f0366e276a693ab9a9b4b8f63e",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
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}