Spring 2027

Statistical Methods for Bioscience I

Statistical Methods for Bioscience I covers descriptive statistics, distributions, normal inference, power, one-way ANOVA, simple linear regression, categorical data, and non-parametric methods.

no offering record for this termCredits unavailable
Recorded instructors · Spring 2027 No instructors listed

Summary

1 / 7

Past student reviews · Debraj Das

One student found the course material not very difficult, but noted that exams accounted for 80% of the total grade.

Grade history

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

Prerequisites

Course map

Graduate/professional standing

  • Graduate/professional standing
F&WECOL/STAT 571 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
  • Graduate/professional standing

Professors

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

BRET HANLON is recorded teaching in Fall 2010, Fall 2011. Recorded history may be incomplete and does not establish a future schedule.

BRET LARGET is recorded teaching in Fall 2010, Fall 2011. Recorded history may be incomplete and does not establish a future schedule.

CECILE ANE is recorded teaching in Fall 2006, Fall 2007, Fall 2008, Fall 2009, Fall 2014, Fall 2017, Fall 2023. Recorded history may be incomplete and does not establish a future schedule.

DEBRAJ DAS is recorded teaching in 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

Spring 2027

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SectionModeEnrolled / capacityWaitlist

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

Meeting source records
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Student experience

the class

Past student reviews · Bret Larget

Students described the lectures as well-planned and easy to understand, with relevant assignments that prepared them for fair exams.

Recent recorded grades — Fall 2023: 3.44 GPA, 64.0% A/AB (n=111 letter grades); Fall 2024: 3.52 GPA, 73.3% A/AB (n=86 letter grades); Fall 2025: 3.47 GPA, 61.5% A/AB (n=78 letter grades).

difficulty & workload

Past student reviews · Debraj Das

One student found the course material not very difficult, but noted that exams accounted for 80% of the total grade.

Past student reviews · Bret Larget

A student found it frustrating that lecture slides were often not posted until a few hours before class, making it hard to print them in advance.

Topics

  • Descriptive statistics, distributions, one- and two-sample normal inference, power, one-way ANOVA, simple linear regression, categorical data, non-parametric methods; underlying assumptions and diagnostic work.

Skills

  • Descriptive statistics, distributions, one- and two-sample normal inference, power, one-way ANOVA, simple linear regression, categorical data, non-parametric methods; underlying assumptions and diagnostic work.

Grades

Latest available · Fall 2025— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

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

1316 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

No offering records for the selected term.

Raw records 
[]
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
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Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "98e28ae30830c789ec2b7ef2895b97fbca73921834b18c8d5181149b2850a845",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}