Fall 2026

Simulation and Probabilistic Modeling

ISYE 320 teaches analysis of stochastic systems through analytic methods and computer simulation, covering queuing, Markov processes, and simulation project management.

offering recorded3 credits
Recorded instructors · Fall 2026 Qiaomin Xie3.5/5

Summary

1 / 6

Homework is incredibly difficult with no related examples in class or lab, and students are expected to have significant prior knowledge.

Grade history

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

Prerequisites

Course map

(MATH/​STAT 309,STAT 311,MATH/​STAT 431, 531 or concurrent enrollment) and (I SY E 210,E C E 331,STAT/​MATH 310,STAT 312, 324, 371, or concurrent enrollment) and (MATH 320, 340, or concurrent enrollment), or member of Engineering Guest Students

ISYE 320 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: 1.00/5 from 1 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.

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

Qiaomin Xie is described as sweet but not a great professor, with lectures that are not amazing and cover potentially irrelevant material. Reviewers note that homework is incredibly difficult due to a lack of related examples in class or lab and insufficient help from the professor and TA.

Recent recorded grades — Fall 2023: 3.68 GPA, 88.6% A/AB (n=44 letter grades); Spring 2025: 3.45 GPA, 78.9% A/AB (n=38 letter grades); Spring 2026: 3.69 GPA, 90.9% A/AB (n=44 letter grades). Includes jointly taught sections.

Historical instructors & teaching patterns

Qiaomin Xie is the current instructor, but no reviews exist for her teaching of this course. Historical reviews for Chen Wang, Xin Wang, and Amanda Smith describe varied experiences, ranging from clear explanations to slow pacing and high praise for exam preparation.

AMANDA SMITH is recorded teaching in Fall 2019, Fall 2020, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.

CHEN WANG is recorded teaching in Spring 2012. Recorded history may be incomplete and does not establish a future schedule.

QIAOMIN XIE is recorded teaching in Spring 2022, Spring 2023, Fall 2023, Spring 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

XIN WANG is recorded teaching in Fall 2016, Fall 2017, Fall 2018. 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
LEC 001Classroom Instruction75 / 713

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

Qiaomin Xie is described as sweet but ineffective, with unclear lectures and unhelpful support, leading to a poor overall experience.

Recent recorded grades — Spring 2025: 3.45 GPA, 78.9% A/AB (n=38 letter grades); Fall 2025: 3.63 GPA, 84.5% A/AB (n=71 letter grades); Spring 2026: 3.69 GPA, 90.9% A/AB (n=44 letter grades).

difficulty & workload

Homework is incredibly difficult with no related examples in class or lab, and students are expected to have significant prior knowledge.

Lectures cover irrelevant material, and the professor and TA provide insufficient help, making the course frustrating and poorly supported.

Topics

  • Models of arrival and service processes.
  • State spaces and state transition probabilities.
  • Queuing and manufacturing system simulation.
  • Continuous time Markov analysis.
  • Simulation project management and testing.

Skills

  • Analytic analysis of stochastic systems.
  • Simulation of queuing and manufacturing systems.
  • Continuous time Markov analysis.
  • Simulation project management and testing.

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 · 0.21 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.

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Selected offering source records
ISYE 320 · Fall 2026

Simulation and Probabilistic Modeling

Recorded 2026-09-07
Raw records
[
  {
    "run_id": "20260907T155543-ce3781c4",
    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "offering_id": "1272:490:010231",
    "course_id": "ISYE 320",
    "course_uid": "course_10d2c585c41b0b82531af186",
    "term_id": "1272",
    "source_course_id": "010231",
    "source_subject_id": "490",
    "title": "Simulation and Probabilistic Modeling",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Fall, Spring"
  }
]
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 2026-09-07

Download the original dataset
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "df10648e619df0ee61265c7deca2117ab07a3df1d7381fb8b1b412a5f2bad6a8",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}