Spring 2027

Statistical Methods Applied to Education II

Covers analysis of variance and covariance, multiple linear regression, chi-square, and nonparametric techniques in educational statistics.

offering recorded3 credits
Recorded instructors · Spring 2027 Jodi Wollack

Summary

1 / 2

Recent recorded grades — Spring 2024: 3.96 GPA, 96.5% A/AB (n=57 letter grades); Spring 2025: 3.96 GPA, 100.0% A/AB (n=52 letter grades); Spring 2026: 3.88 GPA, 100.0% A/AB (n=37 letter grades).

Grade history

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

All recorded terms · compare terms & instructors

Prerequisites

Course map

ED PSYCH 760

EDPSYCH 761 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

Recent recorded grades — Spring 2024: 3.96 GPA, 96.5% A/AB (n=57 letter grades); Spring 2025: 3.96 GPA, 100.0% A/AB (n=52 letter grades); Spring 2026: 3.88 GPA, 100.0% A/AB (n=37 letter grades).

Historical instructors & teaching patterns

JODI WOLLACK is recorded teaching in Spring 2018, Spring 2019, Spring 2020, Spring 2022, Spring 2023, Spring 2024, Spring 2025, 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 / 300
LEC 002Classroom Instruction0 / 300
LAB 301Classroom Instruction0 / 200
LAB 302Classroom Instruction0 / 200

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

Recent recorded grades — Spring 2024: 3.96 GPA, 96.5% A/AB (n=57 letter grades); Spring 2025: 3.96 GPA, 100.0% A/AB (n=52 letter grades); Spring 2026: 3.88 GPA, 100.0% A/AB (n=37 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Analysis of variance and covariance
  • Multiple linear regression
  • Chi-square
  • Nonparametric techniques

Skills

  • Analysis of variance and covariance
  • Multiple linear regression
  • Chi-square techniques
  • Nonparametric techniques

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 · 0.04 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.

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Selected offering source records
EDPSYCH 761 · Spring 2027

Statistical Methods Applied to Education II

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": "1274:315:006217",
    "course_id": "EDPSYCH 761",
    "course_uid": "course_488bc55cdeeb53783da10dab",
    "term_id": "1274",
    "source_course_id": "006217",
    "source_subject_id": "315",
    "title": "Statistical Methods Applied to Education II",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Occasionally"
  }
]
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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 2026-10-14

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 1
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "392a40529b57cb9037b226373ec6bbe896369711f9c10744f28bdf0a53c50dbf",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}