Applied Statistics Iii
11:40am–12:55pm
SCHOOL OF SOCIAL WORK SSW 903
Seat data provenance: Directory as of August 23, 2026 at 4:00 AM
Description
Prerequisites: STAT GR6102 Modern Bayesian methods offer an amazing toolbox for solving science and engineering problems. We will go through the book Bayesian Data Analysis and do applied statistical modeling using Stan, using R (or Python or Julia if you prefer) to preprocess the data and postprocess the analysis. We will also discuss the relevant theory and get to open questions in model building, computing, evaluation, and expansion. The course is intended for students who want to do applied statistics and also those who are interested in working on statistics research problems.
Reviews
Course experience
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Instructor quality
n=6, 2001–2011
Aggregated across every course Andrew Gelman has taught.
Teaching quality
4.8 / 5
Grading fairness
No signal
Workload
4.0 / 5 · Heavy
Difficulty
3.4 / 5 · Moderate
Overall sentiment
In your week
Where it meets
Flat map — motion reduced
Workload and grading
- Grading
- Not published
- Format
- Not published
- Credits
- 4 credits
Reported workload
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