Advanced Quantitative Methods
Advanced Quantitative Methods covers selected topics in analyzing spatial distributions with an emphasis on multivariate techniques.
Summary
Past student reviews · Song Gao
One student described the class as one of the toughest to understand, noting that lectures went very deep into the material and required significant effort to grasp.
What you’ll be able to do
Discuss statistical concepts, methods, and techniques.
Conduct various staining analyses on geographic data.
Use R script programming for spatiotemporal statistical analysis.
Solve practical problems using statistics and spatiotemporal analysis methods.
Discuss the latest literature about the newly developed R scripts for geospatial data analysis.
Source: UW Guide
Grade history
↗All recorded terms · compare terms & instructors
Prerequisites
Course mapJunior standing or GEOG 360
- Junior standing
- GEOG 360
This is a best-effort interpretation; check the catalog requirements above.
Prerequisite text tree
- Any of
- Junior standing
- GEOG 360
Professors
Spring 2027No instructors recorded for this selection.
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
Spring 2027Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.
Meeting source records
Student experience
the class
Past student reviews · Song Gao
Students found the course effectively designed to prepare them for spatial statistics and machine learning, with a helpful emphasis on theory in lectures and R in labs.
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
Past student reviews · Song Gao
One student described the class as one of the toughest to understand, noting that lectures went very deep into the material and required significant effort to grasp.
Past student reviews · Song Gao
Reviewers noted that Prof. Gao utilized the latest technology and advanced methods with R in practice, making the class feel cool and educational.
Topics
- Analysis of spatial distributions
- Multivariate techniques
- Spatiotemporal statistical analysis using R
Skills
- Discussing statistical concepts, methods, and techniques
- Conducting various staining analyses on geographic data
- Using R script programming for spatiotemporal statistical analysis
- Solving practical problems using statistics and spatiotemporal analysis methods
Grades
Latest available · Fall 2025— not enough history to project Spring 2027.
Grade distribution · % of letter grades
Grades over time
Through Fall 2025
More grade details Grade mix, volume & source data
Not enough comparable courses for Spring 2027 in UW–Madison.
Sources & history
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
No offering records for the selected term.
Raw records
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Student reviews
Original comments behind the course and instructor summaries.
Read original reviews
Grade history
Recorded grade distributions by term, section, and instructor.
Explore recorded gradesRecorded 2026-10-14
Model outputs & technical records
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
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"requirements_status": "needs_review",
"dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
"observed_at": "2026-10-14 17:50:09.728220+00:00"
}