Business Statistics Using Python
Recorded 2026-09-07 Fall 2026
Business Statistics Using Python
A statistics primer for business analysis covering probability, estimation, inference, correlation, and regression using Python.
Recorded instructors · Fall 2026 No instructors listed
Summary
1 / 2
Recent recorded grades — Spring 2025: 3.82 GPA, 88.1% A/AB (n=42 letter grades); Fall 2025: 3.92 GPA, 95.0% A/AB (n=40 letter grades); Spring 2026: 3.79 GPA, 95.2% A/AB (n=21 letter grades).
Grade history
↗ average GPA
letter grades
letter grades
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AB
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All recorded terms · compare terms & instructors
Prerequisites
Course mapGraduate/professional standing or declared in graduate Business Exchange program
- Graduate/professional standing or declared in graduate Business Exchange program
“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 or declared in graduate Business Exchange program
Professors
Fall 2026No instructors recorded for this selection.
Historical instructors & teaching patterns
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Calendar & sections
Fall 2026Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.
Meeting source records
No records available.
Student experience
the class
Recent recorded grades — Spring 2025: 3.82 GPA, 88.1% A/AB (n=42 letter grades); Fall 2025: 3.92 GPA, 95.0% A/AB (n=40 letter grades); Spring 2026: 3.79 GPA, 95.2% A/AB (n=21 letter grades).
difficulty & workload
No workload feedback recorded.
Topics
Skills
Grades
Latest available · Spring 2026— not enough history to project Fall 2026.
Grade distribution · % of letter grades
A
AB
B
BC
C
D
F
Grades over time
Through Spring 2026
More grade details Grade mix, volume & source data
Not enough comparable courses for Fall 2026 in UW–Madison.
Sources & history
UW–Madison
Catalog & offerings
Descriptions, prerequisites, and recorded course offerings.
Catalog observation history
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Selected offering source records
Raw records
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]Rate My Professors
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.
Explore recorded gradesModel outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
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