Fall 2026

Business Analytics I

Business Analytics I teaches quantitative intuition, database visualization, probability, hypothesis testing, regression, and simulation for business decision-making.

offering recorded3 credits

Summary

1 / 7

The course features difficult exams and time-consuming Excel case reports. Students emphasize attending lectures and completing practice problems early to prepare for assessments.

Grade history

average GPA
letter grades
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AB
B
BC
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F

All recorded terms · compare terms & instructors

Prerequisites

Course map

(GEN BUS 106 or concurrent enrollment) and (MATH 211, 217, or 221), or declared in undergraduate Business Exchange program

GENBUS 306 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
/5Adjusted rating
/5RMP difficulty
captured reviews
About this rating

Raw average: 4.51/5 from 69 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: 4.5/5 raw quality · 3.1/5 difficulty · 31 reviews

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

Richard Crabb is a passionate, funny lecturer who uses real-world applications to engage students. Reviewers praise his clarity and flexibility, noting he wants everyone to succeed. The course material is described as challenging, but his engaging style makes the class interesting.

Crabb provides extensive practice problems and lecture videos, which reviewers find helpful for exam preparation. The course relies on exams and Excel case studies. While the material is challenging, consistent work on cases and practice problems leads to success.

Recent recorded grades — Spring 2025: 3.27 GPA, 51.2% A/AB (n=170 letter grades); Fall 2025: 3.31 GPA, 57.0% A/AB (n=435 letter grades); Spring 2026: 3.25 GPA, 47.7% A/AB (n=478 letter grades). Includes jointly taught sections.

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

Raw average: 3.82/5 from 28 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: 3.3/5 raw quality · 2.8/5 difficulty · 8 reviews

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

Hessam Bavafa is praised for making lectures interesting and funny, teaching the material well, though one reviewer emphasized that attending lectures is necessary due to sparse slides. Conversely, reviewers criticize his slow email response times and lack of care for student grades, though others find him caring. One advised avoidance due to poor explanations, while another noted that case reports require time.

Recent recorded grades — Fall 2023: 3.20 GPA, 49.6% A/AB (n=560 letter grades); Spring 2025: 3.26 GPA, 53.9% A/AB (n=219 letter grades); Fall 2025: 3.31 GPA, 57.0% A/AB (n=435 letter grades). Includes jointly taught sections.

Historical instructors & teaching patterns

Historical reviews of Anita Mukherjee: Anita Mukherjee is described as engaging, enthusiastic, and effective, with clear directions and fair grading. Reviewers highlight her ability to make statistics accessible and her supportive nature, though some note the workload can be heavy due to Excel-based cases.

ANITA MUKHERJEE is recorded teaching in Fall 2016, Fall 2017, Fall 2018, Fall 2019, Fall 2020, Fall 2021, Fall 2022, Spring 2023. Recorded history may be incomplete and does not establish a future schedule.

HESSAM BAVAFA is recorded teaching in Fall 2016, Fall 2017, Fall 2018, Fall 2019, Fall 2020, Fall 2022, Spring 2023, Fall 2023, Spring 2025, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.

RICHARD CRABB is recorded teaching in 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, Fall 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

Fall 2026

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
DIS 301Classroom Instruction42 / 430
DIS 304Classroom Instruction43 / 434
DIS 305Classroom Instruction42 / 432
DIS 308Classroom Instruction42 / 433
DIS 309Classroom Instruction43 / 432
DIS 310Classroom Instruction43 / 430
DIS 312Classroom Instruction43 / 432
DIS 306Classroom Instruction43 / 433
LEC 002Classroom Instruction128 / 1299
LEC 004Classroom Instruction129 / 1295
LEC 001Classroom Instruction128 / 1291
LEC 003Classroom Instruction127 / 1295
DIS 302Classroom Instruction43 / 431
DIS 303Classroom Instruction43 / 430
DIS 307Classroom Instruction42 / 430
DIS 311Classroom Instruction43 / 433

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

Meeting source records

Student experience

the class

Richard Crabb delivers engaging lectures with real-world applications. Hessam Bavafa makes classes interesting but receives mixed feedback regarding email responsiveness.

Recent recorded grades — Spring 2025: 3.27 GPA, 52.7% A/AB (n=484 letter grades); Fall 2025: 3.31 GPA, 57.0% A/AB (n=435 letter grades); Spring 2026: 3.25 GPA, 47.7% A/AB (n=478 letter grades).

difficulty & workload

The course features difficult exams and time-consuming Excel case reports. Students emphasize attending lectures and completing practice problems early to prepare for assessments.

Students appreciate the helpful practice materials and clear exam guidance. However, some report frustration with slow email responses and subjective grading on case write-ups.

Topics

  • Probability and decision under uncertainty
  • Big data and data mining concepts
  • Business case studies

Skills

  • Database management and visualization
  • Statistical hypothesis testing and regression
  • Simulation methods
  • Data communication

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 · 0.11 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.

Selected offering source records
GENBUS 306 · Fall 2026

Business Analytics I

Recorded 2026-09-07
Raw records
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  {
    "run_id": "20260907T155543-ce3781c4",
    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "offering_id": "1272:231:024534",
    "course_id": "GENBUS 306",
    "course_uid": "course_801a8dc807b21e1c6c93cc3f",
    "term_id": "1272",
    "source_course_id": "024534",
    "source_subject_id": "231",
    "title": "Business Analytics I",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Not Applicable"
  }
]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Model 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
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "2354b78aa3ddd3d2f9029b1cf209e5b5a6a2abda4e3f8fef7d9601ea21062b08",
  "requirements_status": "needs_review",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}