Fall 2026

Advanced Quantitative Methods

GEOG 560 covers advanced quantitative methods for analyzing spatial distributions using multivariate techniques.

offering recorded3 credits
Recorded instructors · Fall 2026 Song Gao4.3/5

Summary

1 / 6

The course is considered tough to understand initially, with deep lectures covering complex formulas. Labs are used to efficiently learn R, supporting those with limited prior experience.

Grade history

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

Prerequisites

Course map

Junior standing or GEOG 360

    • Junior standing
    • GEOG 360
    take one
GEOG 560

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

Prerequisite text tree
  • Any of
    • Junior standing
    • GEOG 360

Professors

Fall 2026
/5Adjusted rating
/5RMP difficulty
captured reviews
About this rating

Raw average: 4.71/5 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: 5.0/5 raw quality · 3.8/5 difficulty · 5 reviews

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

Song Gao teaches GEOG 560 with high enthusiasm and deep knowledge of geospatial data science, R, and spatial statistics. Reviewers praise his patience and the course's effective design for preparing students with limited prior experience in these areas.

Recent recorded grades — Fall 2019: 3.90 GPA, 100.0% A/AB (n=15 letter grades); Fall 2022: 4.00 GPA, 100.0% A/AB (n=6 letter grades); Fall 2025: 3.94 GPA, 100.0% A/AB (n=26 letter grades).

Historical instructors & teaching patterns

SONG GAO is recorded teaching in Spring 2018, Spring 2019, Fall 2019, Fall 2022, Fall 2025. 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 Instruction45 / 4210

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

Song Gao’s GEOG 560 course effectively prepares students for spatial statistics and machine learning through advanced R methods and theory. Reviewers report high learning value and professional readiness.

Recent recorded grades — Fall 2019: 3.90 GPA, 100.0% A/AB (n=15 letter grades); Fall 2022: 4.00 GPA, 100.0% A/AB (n=6 letter grades); Fall 2025: 3.94 GPA, 100.0% A/AB (n=26 letter grades).

difficulty & workload

The course is considered tough to understand initially, with deep lectures covering complex formulas. Labs are used to efficiently learn R, supporting those with limited prior experience.

Students describe Professor Gao as patient, talented, and enthusiastic. His deep knowledge and engaging lectures help maintain motivation despite the course's difficulty.

Topics

  • Spatial distributions
  • Multivariate techniques

Skills

  • Analysis of spatial distributions
  • Application of multivariate techniques

Grades

Latest available · Fall 2025— not enough history to project Fall 2026.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Fall 2025

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

Observations at scan time; dates do not imply when a catalog change took effect.

Selected offering source records
GEOG 560 · Fall 2026

Advanced Quantitative Methods

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": "1272:416:008338",
    "course_id": "GEOG 560",
    "course_uid": "course_1049f8ea4b6f06a27858f913",
    "term_id": "1272",
    "source_course_id": "008338",
    "source_subject_id": "416",
    "title": "Advanced Quantitative Methods",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Spring"
  }
]
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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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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": "fa12b6595cb0859f41da4b027a5170ae78444697882769ff791704bf273236b5",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}