Spring 2027

Risk Analytics and Behavioral Science

Risk Analytics and Behavioral Science covers decision analysis as a structured rational approach to making decisions under uncertainty, focusing on navigating risk through question formulation and information processing.

offering recorded3 credits
Recorded instructors · Spring 2027 Philip Cook

Summary

1 / 6

Past student reviews · Justin Sydnor

Past students reported four difficult Excel homework assignments and four open-book, open-note online unit exams, which they found manageable despite being conceptual.

What you’ll be able to do

  • Recognize situations where potential biases in perceptions, understanding, and decisions related to risk management are likely to arise

  • Articulate the behavioral factors and psychological processes that may generate bias in that situation

  • Employ appropriate decision/evaluation process and business analytics to help improve decisions in the face of potential bias. These techniques include Monte Carlo Simulation, Decision Tree Analysis, and Expected Value Maximization

  • Diagnose risk management failures for corporations and suggest techniques and alternative management approaches that could mitigate these risk management issues

Source: UW Guide

Grade history

↗
average GPA
letter grades
A
AB
B
BC
C
D
F

All recorded terms · compare terms & instructors

Prerequisites

Course map

(R M I 300 or graduate/professional standing) and (GEN BUS 306, 704, 705,ECON 310,MATH/​STAT 309, 431, or MATH 331), or declared in the Business Exchange program

RMI 660

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Spring 2027

Recent recorded grades — Spring 2024: 3.45 GPA, 65.3% A/AB (n=95 letter grades); Spring 2025: 3.48 GPA, 66.3% A/AB (n=89 letter grades); Spring 2026: 3.49 GPA, 63.0% A/AB (n=92 letter grades).

Historical instructors & teaching patterns

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

PHILIP COOK is recorded teaching in Spring 2024, Spring 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

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 550
LEC 002Classroom Instruction0 / 540
LEC 003Classroom Instruction0 / 550

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 · Justin Sydnor

Past students described the course as a fun, interesting mix of psychology, economics, and analytics, with lectures often feeling more like discussions.

Recent recorded grades — Spring 2024: 3.45 GPA, 65.3% A/AB (n=95 letter grades); Spring 2025: 3.48 GPA, 66.3% A/AB (n=89 letter grades); Spring 2026: 3.49 GPA, 63.0% A/AB (n=92 letter grades).

difficulty & workload

Past student reviews · Justin Sydnor

Past students reported four difficult Excel homework assignments and four open-book, open-note online unit exams, which they found manageable despite being conceptual.

Past student reviews · Justin Sydnor

Students found past instructor Justin Sydnor approachable and willing to help, though some noted that feedback could arrive late or explanations were occasionally overly detailed.

Topics

  • Navigating uncertainty in business and risk management.
  • Behavioral factors and psychological processes generating bias.
  • Decision evaluation processes including Monte Carlo Simulation and Decision Tree Analysis.

Skills

  • Formulating questions, identifying valuable information, processing signals vs. noise, and structuring uncertain environments.
  • Applying Monte Carlo Simulation, Decision Tree Analysis, and Expected Value Maximization.
  • Diagnosing corporate risk management failures and suggesting mitigation techniques.

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.

7 earlier forecasts · 0.16 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
RMI 660 · Spring 2027

Risk Analytics and Behavioral Science

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": "1274:241:024401",
    "course_id": "RMI 660",
    "course_uid": "course_c47d8e0ceec23e8339985140",
    "term_id": "1274",
    "source_course_id": "024401",
    "source_subject_id": "241",
    "title": "Risk Analytics and Behavioral Science",
    "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
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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": "fd4b2b0ed874a471039c0153cec70d6562e5b70f3612cfca449e24e9b94568d8",
  "requirements_status": "needs_review",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}