Spring 2027

Data to Decisions

Data to Decisions explores statistical inference and data analytics tools, reviewing foundations of statistics, machine learning, and probability theory applied to business examples using Excel and R.

offering recorded2–3 credits
Recorded instructors · Spring 2027 No instructors listed

Summary

1 / 4

Recent recorded grades — Spring 2025: 3.52 GPA, 76.0% A/AB (n=25 letter grades); Fall 2025: 3.74 GPA, 85.7% A/AB (n=84 letter grades); Spring 2026: 3.76 GPA, 89.5% A/AB (n=19 letter grades).

What you’ll be able to do

  • Read, clean, create new datasets

  • Describe the resulting data by computing and interpreting summary statistics, and via visualization tools

  • Describe uncertainty and risk using the language of probability theory

  • Perform hypothesis tests common in business applications

  • Perform Monte Carlo simulations

  • Estimate cross-sectional and time-series models for forecasting purposes and select among competing models via cross-validation

  • Apply machine learning methods in the context of simple examples

Source: UW Guide

Grade history

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

Prerequisites

Course map

Declared in an MBA program

  • Declared in an MBA program
GENBUS 704 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
  • Declared in an MBA program

Professors

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

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SectionModeEnrolled / capacityWaitlist

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Meeting source records
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Student experience

the class

Recent recorded grades — Spring 2025: 3.52 GPA, 76.0% A/AB (n=25 letter grades); Fall 2025: 3.74 GPA, 85.7% A/AB (n=84 letter grades); Spring 2026: 3.76 GPA, 89.5% A/AB (n=19 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Foundations of statistics, machine learning, and probability theory
  • Application of statistical concepts to canonical business examples
  • Use of Excel and R for data analytics

Skills

  • Reading, cleaning, and creating new datasets
  • Computing and interpreting summary statistics and using visualization tools
  • Performing hypothesis tests for business applications
  • Performing Monte Carlo simulations
  • Estimating cross-sectional and time-series models for forecasting and selecting models via cross-validation
  • Applying machine learning methods to simple examples

Grades

Latest available · Spring 2026— 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 Spring 2026

More grade details Grade mix, volume & source data

Not enough comparable courses for Spring 2027 in UW–Madison.

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
GENBUS 704 · Spring 2027

Data to Decisions

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": "1274:231:002971",
    "course_id": "GENBUS 704",
    "course_uid": "course_895b29b6b7e498e159e85948",
    "term_id": "1274",
    "source_course_id": "002971",
    "source_subject_id": "231",
    "title": "Data to Decisions",
    "credits_min": 2,
    "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.

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Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "8e924411f2bff3763a58e85bd28d1aed99564ae2136b6ac26cb78d88afd2f26b",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}