Spring 2027

Statistical Experimental Design

STAT 424 covers the design and analysis of experiments, including randomization, blocking, factorial designs, and response surfaces, with a focus on engineering applications and A/B testing.

offering recorded3 credits
Recorded instructors · Spring 2027 No instructors listed

Summary

1 / 6

Past student reviews · Wei-Yin Loh

One student reported that the course required reading through limited lecture slides, with a midterm weighted at 40% and a final at 50% of the total grade.

What you’ll be able to do

  • Describe key concepts in the design and analysis of experiments.

  • Generate experimental designs and apply appropriate analysis techniques.

  • Compare different experimental design and analysis methods in various scenarios.

  • Apply experimental design and analysis methods in real-world projects.

  • Implement experimental design and analysis methods in statistical software like R.

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

(MATH/​STAT 310,STAT 333, or 340) or (declared in Mechanical Engineering BS and one ofSTAT 240, 301, 302, 312, 324, 371, orI SY E 210), or graduate/professional standing

STAT 424 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

Professors

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

EDWARD ERKER is recorded teaching in Spring 2022. Recorded history may be incomplete and does not establish a future schedule.

NIMAL WICKREMASINGHE is recorded teaching in Fall 2024. Recorded history may be incomplete and does not establish a future schedule.

PIXU SHI is recorded teaching in Spring 2019, Spring 2020. Recorded history may be incomplete and does not establish a future schedule.

WEI-YIN LOH is recorded teaching in Fall 2006, Spring 2009, Spring 2010, Fall 2010, Fall 2011, Fall 2015, Fall 2022. 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 / 660
DIS 311Classroom Instruction0 / 220
DIS 312Classroom Instruction0 / 220
DIS 313Classroom Instruction0 / 220

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

Past student reviews · Peter Chien

Students found the material manageable and the assessments predictable, noting that the course was relatively easy to navigate despite some criticism of lecture quality.

Recent recorded grades — Spring 2025: 3.55 GPA, 68.6% A/AB (n=51 letter grades); Fall 2025: 3.55 GPA, 76.3% A/AB (n=59 letter grades); Spring 2026: 3.67 GPA, 76.7% A/AB (n=60 letter grades).

difficulty & workload

Past student reviews · Wei-Yin Loh

One student reported that the course required reading through limited lecture slides, with a midterm weighted at 40% and a final at 50% of the total grade.

Past student reviews · Peter Chien

A past student found lectures unhelpful and learned primarily through the textbook and TAs, expressing frustration that the instructor skimmed project proposals without detecting errors.

Topics

  • Principles of randomization, blocking, and replication
  • Randomized blocking and Latin square designs
  • Factorial designs and response surface methodology
  • Engineering applications
  • Digital transformation and A/B testing

Skills

  • Generating experimental designs and applying analysis techniques
  • Implementing experimental design methods in R

Grades

Historical instructor

Spring 2027 · Projected

Before grades are released

– average GPA

Approximate 80% prediction interval

About this estimate

The course’s semester-average GPA, not an individual student’s grade. The center uses 5 same-season terms, weighted toward recent results.

The range uses the finite-sample 80th-percentile rank of absolute errors from earlier same-season forecasts. Each forecast uses only records from earlier terms. At least four forecasts are required; bounds are rounded outward and limited to 0–4. This is an empirical estimate: changing instructors or grading policies can reduce its coverage.

8 earlier forecasts · 0.13 GPA average error.

Grades over time

Through Spring 2027

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
STAT 424 · Spring 2027

Statistical Experimental Design

Recorded 2026-10-14
Raw records 
[
  {
    "run_id": "20261014T203208-0851c9a1",
    "semester": "1274",
    "observed_at": "2026-10-14 17:50:09.728220+00:00",
    "offering_id": "1274:932:018463",
    "course_id": "STAT 424",
    "course_uid": "course_3c746e3add116a6aa2b49441",
    "term_id": "1274",
    "source_course_id": "018463",
    "source_subject_id": "932",
    "title": "Statistical Experimental Design",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Fall, Spring, Summer"
  }
]
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 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "a934be5d4b43506e8e0ff2baffa55f54908023d518f66fa54639bc2aa4357f20",
  "requirements_status": "needs_review",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}