STAT 226Spatial Statistics
Introduction to the analysis of spatial data: theory of correlation structures and variograms; kriging and Gaussian processes; Markov random fields; fitting models to data; computational techniques; frequentist and Bayesian approaches. (Formerly AMS 245.)
Prerequisite(s): STAT 207. Enrollment is restricted to graduate students.
Find a section and add it to your scheduleLive seat counts, time-conflict checks and the walk from your previous class.
When it runs
Spring 2026Open Spring 2026
| Section | Type | When | Where | Instructor | Seats |
|---|---|---|---|---|---|
| 01 | Lecture | Tue Thu 1:30pm–3:05pm | Crown Clrm 105 | B. Sanso | Closed 11/10 |
Who teaches it
| Instructor | Rating | Difficulty | Would take again | Reviews |
|---|---|---|---|---|
| Bruno Sanso | 2.2 / 5 | 3.4 / 5 | 27% | 52 |
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