Spring 2027

Basic Statistics for Psychology

An introductory statistics course covering descriptive measures, probability, hypothesis testing, t-tests, Chi-square, regression, correlation, and one-way ANOVA.

offering recorded3 credits
Recorded instructors · Spring 2027 Jonathan Gallimore3.2/5

Summary

1 / 6

Past student reviews · Jonathan Gallimore

Students reported having to do a lot of self-teaching to succeed, and the course required a significant amount of work to keep up with the material.

What you’ll be able to do

  • Explain why data beat anecdotes.

  • Understand why association is not causation

  • Explain the fundamental concepts and apply the basic procedures that underlie descriptive and inferential statistics

  • Interpret and draw conclusions from graphical displays and standard output from statistical software packages.

  • Understand why statistical significance does not necessarily imply practical importance.

  • Demonstrate an awareness of ethical issues associated with sound statistical practice.

Source: UW Guide

Grade history

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

Prerequisites

Course map

Satisfied Quantitative Reasoning (QR) A and (PSYCH 202 or concurrent enrollment)

PSYCH 210 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
Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 3.19/5 from 200 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: 3.1/5 raw quality · 3.2/5 difficulty · 38 reviews

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

Past student reviews · Jonathan Gallimore

Jonathan Gallimore used a flipped classroom model, requiring students to self-teach from modules rather than relying on live lectures. Reviewers described the workload as heavy, with some feeling constantly behind, while others found the independent studying helped them understand topics better.

Exams were long and sometimes difficult, including a 120-question final in 120 minutes. Gallimore offered substantial extra credit to help students manage grades, though several reviewers criticized his passive-aggressive comments and public callouts during class.

Recent recorded grades — Spring 2025: 3.24 GPA, 64.1% A/AB (n=92 letter grades); Fall 2025: 3.25 GPA, 59.4% A/AB (n=64 letter grades); Spring 2026: 3.03 GPA, 52.7% A/AB (n=131 letter grades). Includes jointly taught sections.

Historical instructors & teaching patterns

Past student reviews · Chelsea Andrews, Jacqueline Fulvio

Chelsea Andrews managed to create a low-stress environment with assignments due daily, while Jacqueline Fulvio explained the process of statistics clearly but wished for more depth on conceptual aspects. Students noted that Fulvio required textbook reading to understand definitions, whereas Andrews made the information easy to understand.

EMILY WARD is recorded teaching in Spring 2018, Fall 2018, Fall 2019, Fall 2021. Recorded history may be incomplete and does not establish a future schedule.

JACQUELINE FULVIO is recorded teaching in Spring 2013, Fall 2013, Spring 2014, Fall 2014, Spring 2015, Spring 2023. Recorded history may be incomplete and does not establish a future schedule.

JEFFREY HENRIQUES is recorded teaching in Fall 2012, Spring 2013, Fall 2013, Spring 2014, Fall 2014, Spring 2015, Fall 2015, Spring 2016, Fall 2016, Spring 2017, Fall 2017, Spring 2018, Fall 2018, Spring 2019, Fall 2019, Spring 2020, Fall 2020, Fall 2021, Spring 2022, Fall 2022, Spring 2023, Fall 2023, Spring 2024, Fall 2024, Spring 2025. Recorded history may be incomplete and does not establish a future schedule.

JONATHAN GALLIMORE is recorded teaching in Fall 2019, Spring 2020, Fall 2020, Fall 2021, Spring 2022, 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.

MATTHEW ANDRZEJEWSKI is recorded teaching in Fall 2011, Spring 2012. Recorded history may be incomplete and does not establish a future schedule.

REBECCA ADDINGTON is recorded teaching in Spring 2007, Fall 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2014, Fall 2014, Spring 2015, Fall 2015, Spring 2016, Fall 2016, Spring 2017, Fall 2017, Spring 2018, Fall 2018, Spring 2019, Fall 2019, Spring 2020, Fall 2020, Fall 2021, Spring 2022, Fall 2022, Spring 2023, Fall 2023, Spring 2024, Fall 2024, Spring 2025. Recorded history may be incomplete and does not establish a future schedule.

RICK JENISON is recorded teaching in Fall 2006, Spring 2007, Fall 2008, Fall 2009, Fall 2010, Spring 2014, Spring 2017. Recorded history may be incomplete and does not establish a future schedule.

STEPHANIE SCHELL is recorded teaching in Fall 2011, Spring 2012, Spring 2013, Fall 2013, Fall 2014, Fall 2015. 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 / 1000
LEC 002Classroom Instruction0 / 1000
LEC 003Classroom Instruction0 / 1000
LEC 004Classroom Instruction0 / 1000

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 · Jonathan Gallimore

Dr. Gallimore taught statistics in a way that made complex material simple and digestible, while clearly outlining exam expectations and providing ample practice resources.

Recent recorded grades — Spring 2025: 3.08 GPA, 50.6% A/AB (n=330 letter grades); Fall 2025: 3.11 GPA, 50.5% A/AB (n=325 letter grades); Spring 2026: 3.43 GPA, 68.0% A/AB (n=341 letter grades).

difficulty & workload

Past student reviews · Jonathan Gallimore

Students reported having to do a lot of self-teaching to succeed, and the course required a significant amount of work to keep up with the material.

Past student reviews · Jonathan Gallimore

Some students found the flipped classroom structure frustrating, noting that Professor Gallimore did not teach during weekly lectures and that the workload could feel overwhelming.

Topics

  • Descriptive statistics, probability, sampling distributions, and hypothesis testing.
  • Inferential tests including t-tests, Chi-square, linear regression, correlation, and one-way ANOVA.

Skills

  • Apply basic procedures of descriptive and inferential statistics.
  • Interpret graphical displays and statistical software output.

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 · 0.17 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
PSYCH 210 · Spring 2027

Basic Statistics for Psychology

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": "1274:820:016367",
    "course_id": "PSYCH 210",
    "course_uid": "course_2b59ae9c5e9641dfdbd15861",
    "term_id": "1274",
    "source_course_id": "016367",
    "source_subject_id": "820",
    "title": "Basic Statistics for Psychology",
    "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
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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 1
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "3ec5ea18958bac324f1630d5da6b99207b2f2dc05aee157c15353db76547d9a4",
  "requirements_status": "needs_review",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}