Fall 2026

Introduction to Statistics for Science and Engineering

Introduction to statistics for science and engineering covering descriptive statistics, probability, hypothesis testing, linear regression, and ANOVA using R.

offering recorded3 credits
Recorded instructors · Fall 2026 Chelsey Green2.8/5Anna MontplaisirBenjamin Crotteau +2 more

Summary

1 / 6

Homework is time-consuming, taking five to six hours per set, and exams are challenging with a time crunch. Students must spend significant time understanding homework to prepare for tests that may differ from practice problems.

Grade history

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

Prerequisites

Course map

MATH 211, 217, or 221. Not open to students with credit forSTAT 371.

STAT 324 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

Fall 2026

Chelsey Green

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

Raw average: 2.68/5 from 115 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: 2.5/5 raw quality · 3.9/5 difficulty · 81 reviews

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

Chelsey Green is praised for clear explanations, patience, and accessibility via office hours and Piazza. Reviewers note her organized notes and helpful lecture recordings support student understanding. However, some find the course material challenging and time-consuming.

Some reviewers criticize Green for disorganization, claiming she provides no notes or textbook and that tests are extremely difficult. These reviews describe the experience as terrible and advise avoiding the course, contrasting sharply with positive feedback on her teaching style.

Recent recorded grades — Spring 2025: 2.95 GPA, 37.3% A/AB (n=383 letter grades); Fall 2025: 2.95 GPA, 36.5% A/AB (n=370 letter grades); Spring 2026: 2.99 GPA, 37.2% A/AB (n=336 letter grades). Includes jointly taught sections.

Recent recorded grades — Fall 2025: 2.92 GPA, 34.6% A/AB (n=179 letter grades); Spring 2026: 3.00 GPA, 37.0% A/AB (n=173 letter grades). Includes jointly taught sections.

Historical instructors & teaching patterns

Historical reviews for STAT 324 describe highly variable experiences. Minjing Tao and John Gillett received praise for clear expectations and organized lectures, while Dong Xia and Sijing Li were criticized for inadequate preparation materials and poor communication. Colin Longhurst and Duzhe Wang were noted for clarity and effort, whereas others like Wesley Brooks struggled with unstructured delivery.

BO YANG is recorded teaching in Fall 2015, Spring 2016. Recorded history may be incomplete and does not establish a future schedule.

BRIAN POWERS is recorded teaching in Fall 2022. Recorded history may be incomplete and does not establish a future schedule.

CHELSEY GREEN is recorded teaching in Fall 2018, Spring 2019, Fall 2022, Spring 2023, Fall 2023, Spring 2024, Fall 2024, Spring 2025, Fall 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

COLIN LONGHURST is recorded teaching in Fall 2015, Spring 2016. Recorded history may be incomplete and does not establish a future schedule.

DEBORAH BENNOR is recorded teaching in Fall 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

DONG XIA is recorded teaching in Fall 2016, Spring 2017. Recorded history may be incomplete and does not establish a future schedule.

DUZHE WANG is recorded teaching in Spring 2019, Fall 2019. Recorded history may be incomplete and does not establish a future schedule.

JARED BROWN is recorded teaching in Fall 2016, Fall 2017. Recorded history may be incomplete and does not establish a future schedule.

JOHN GILLETT is recorded teaching in Fall 2011, Fall 2020, Fall 2021, Fall 2022. Recorded history may be incomplete and does not establish a future schedule.

MINJING TAO is recorded teaching in Spring 2012, Fall 2012, Spring 2013. Recorded history may be incomplete and does not establish a future schedule.

RAHUL MAHAJAN is recorded teaching in Fall 2019. Recorded history may be incomplete and does not establish a future schedule.

SIJING LI is recorded teaching in Fall 2017, Spring 2018. Recorded history may be incomplete and does not establish a future schedule.

WESLEY BROOKS is recorded teaching in Fall 2019. 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 Instruction185 / 2160
LEC 002Classroom Instruction202 / 2160

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

Reviewers describe Chelsey Green as clear, patient, and accessible, with helpful office hours and recorded lectures. They note the class is manageable with open-note exams, though some find the material challenging.

Recent recorded grades — Spring 2025: 2.95 GPA, 37.3% A/AB (n=383 letter grades); Fall 2025: 2.95 GPA, 36.5% A/AB (n=370 letter grades); Spring 2026: 2.99 GPA, 37.2% A/AB (n=336 letter grades).

difficulty & workload

Homework is time-consuming, taking five to six hours per set, and exams are challenging with a time crunch. Students must spend significant time understanding homework to prepare for tests that may differ from practice problems.

Students appreciate open-note exams, recorded lectures, and generous partial credit. Conversely, some reviewers report a lack of provided notes or textbooks, forcing them to organize material themselves, which they found frustrating and difficult.

Topics

  • Descriptive statistics and probability
  • One- and two-sample hypothesis tests and confidence intervals
  • Linear regression and inference
  • Analysis of variance and experimental design

Skills

  • R programming
  • Hypothesis testing and confidence intervals
  • Linear regression and model checking
  • Analysis of variance and experimental design

Grades

Historical instructor

Fall 2026 · 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 · 0.08 GPA average error.

Grades over time

Through Fall 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

1283 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 324 · Fall 2026

Introduction to Statistics for Science and Engineering

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": "1272:932:021159",
    "course_id": "STAT 324",
    "course_uid": "course_06abb97e9793bf858754daa3",
    "term_id": "1272",
    "source_course_id": "021159",
    "source_subject_id": "932",
    "title": "Introduction to Statistics for Science and Engineering",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Fall, Spring"
  }
]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
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.

Download part 1
Model & dataset provenance
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "4d615c14dfb6530f4434c3a9497006dca6ca3577e5b827e8c2f308b3db26748b",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}