Spring 2027

Economic Statistics and Econometrics I

Economic Statistics and Econometrics I covers probability distributions, statistical inference, multiple linear regression, and an introduction to econometric methods.

no offering record for this termCredits unavailable
Recorded instructors · Spring 2027 No instructors listed

Summary

1 / 7

Past student reviews · Yong Cai

Homework problems were described as very easy, contributing to a lower overall difficulty rating for the term.

Grade history

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

Prerequisites

Course map

Graduate/professional standing

  • Graduate/professional standing
ECON 709 used by

“Used by” includes alternatives; linked courses may have other requirements. This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree
  • Graduate/professional standing

Professors

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

BRUCE HANSEN is recorded teaching in Fall 2017, Fall 2019. Recorded history may be incomplete and does not establish a future schedule.

YONG CAI is recorded teaching in Fall 2024, Fall 2025. 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

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SectionModeEnrolled / capacityWaitlist

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

Meeting source records

Student experience

the class

Past student reviews · Yong Cai

The course offered thorough, easy-to-follow lecture notes with numerous helpful example problems, allowing students to feel they learned a lot.

Recent recorded grades — Fall 2023: 3.50 GPA, 64.5% A/AB (n=62 letter grades); Fall 2024: 3.48 GPA, 69.4% A/AB (n=72 letter grades); Fall 2025: 3.56 GPA, 71.2% A/AB (n=59 letter grades).

difficulty & workload

Past student reviews · Yong Cai

Homework problems were described as very easy, contributing to a lower overall difficulty rating for the term.

Past student reviews · Yong Cai

Students noted that lecture notes contained myriad typos, though the material remained helpful and well-structured.

Topics

  • Probability distributions, statistical inference, multiple linear regression, and econometric methods.

Skills

  • Understanding probability distributions, statistical inference, multiple linear regression, and econometric methods.

Grades

Latest available · Fall 2025— 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 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

1316 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

No offering records for the selected term.

Raw records
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Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Model & dataset provenance
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "340c1733f42ddad43f48b5523ad3f5cab671385ab49ce525bd4213b10ac4d1bd",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}