Fall 2026

Applied Categorical Data Analysis

STAT 421 teaches techniques for analyzing categorical response data, including contingency tables and regression modeling, using R.

offering recorded3 credits
Recorded instructors · Fall 2026 Derek Bean3.6/5Jialuo Li

Summary

1 / 6

The workload is relentless, consisting of approximately 66% homework with four to six hours of work per week across multiple large assignments.

Grade history

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

Prerequisites

Course map

STAT 333, 340, graduate/professional standing, or declared in Statistics VISP

  • take one
STAT 421

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

Prerequisite text tree

Professors

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

Raw average: 3.57/5 from 14 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.

For this course: 3.0/5 raw quality · 3.6/5 difficulty · 5 reviews

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

Derek Bean is praised for his organization and clear lectures, though coding demos may need improvement. He provides comprehensive Canvas materials, and attendance is not required.

Reviewers consistently report an overwhelming volume of homework, describing it as relentless and stressful. While some find the content useful and exams stress-free, the heavy workload is a major concern.

Recent recorded grades — Fall 2022: 3.41 GPA, 71.4% A/AB (n=63 letter grades); Fall 2024: 3.51 GPA, 84.1% A/AB (n=82 letter grades); Fall 2025: 3.31 GPA, 58.9% A/AB (n=73 letter grades). Includes jointly taught sections.

Recent recorded grades — Fall 2025: 3.31 GPA, 58.9% A/AB (n=73 letter grades). Includes jointly taught sections.

Historical instructors & teaching patterns

Historical reviews for Wei-Yin Loh praise his energetic teaching and focus on conceptual understanding over memorization, with students finding him fair and inspirational. Conversely, a review for Kam-Wah Tsui describes lectures as hard to follow and unhelpful office hours, labeling the class unnecessarily difficult.

DEREK BEAN is recorded teaching in Fall 2018, Fall 2019, Spring 2020, Fall 2021, Fall 2022, Fall 2024, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.

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

KAM-WAH TSUI is recorded teaching in Fall 2015, Fall 2016. Recorded history may be incomplete and does not establish a future schedule.

WEI-YIN LOH is recorded teaching in Fall 2007, Fall 2008, Fall 2010, Fall 2012, Fall 2014, Fall 2017. 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 Instruction46 / 700
LEC 002Classroom Instruction0 / 20

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

Meeting source records
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Student experience

the class

Derek Bean is organized and provides clear grading criteria, though the course involves a heavy homework load that can be unpleasant for students with busy schedules.

Recent recorded grades — Fall 2022: 3.41 GPA, 71.4% A/AB (n=63 letter grades); Fall 2024: 3.51 GPA, 84.1% A/AB (n=82 letter grades); Fall 2025: 3.31 GPA, 58.9% A/AB (n=73 letter grades).

difficulty & workload

The workload is relentless, consisting of approximately 66% homework with four to six hours of work per week across multiple large assignments.

Students report that the extensive homework improves R proficiency, while take-home exams without time limits provide a stress-free assessment method.

Topics

  • Multidimensional contingency tables and association measures.
  • Logistic and Poisson regression.

Skills

  • Analyzing categorical response data using R.
  • Analyzing multidimensional contingency tables and association measures.
  • Applying logistic and Poisson regression 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
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BC
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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.

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Selected offering source records
STAT 421 · Fall 2026

Applied Categorical Data Analysis

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": "1272:932:018462",
    "course_id": "STAT 421",
    "course_uid": "course_096be5272e913d9005e3298b",
    "term_id": "1272",
    "source_course_id": "018462",
    "source_subject_id": "932",
    "title": "Applied Categorical Data Analysis",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Spring"
  }
]
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.

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Dataset & model

Recorded 2026-09-07

Download the original dataset
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "090a77d8d3da099b4868c56747a4b1db2f1a9085e739e56841b5c824ab271222",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}