Spring 2027

Bayesian Statistics

Advanced Bayesian statistics course covering theory, methods, and computational procedures for data analysis, including MCMC and variational inference.

offering recorded3 credits
Recorded instructors · Spring 2027 Sameer Deshpande

Summary

1 / 3

Recent recorded grades — Spring 2024: 4.00 GPA, 100.0% A/AB (n=30 letter grades); Spring 2025: 3.92 GPA, 96.7% A/AB (n=30 letter grades); Spring 2026: 3.88 GPA, 95.0% A/AB (n=20 letter grades).

What you’ll be able to do

  • Justify the use of probability for coherent uncertainty quantification

  • Explain how Bayesian updating occurs in conjugate models and hierarchical models

  • Compare and contrast the conceptual and practical benefits and challenges of different posterior approximation strategies like MCMC and variational inference

  • Implement posterior approximation algorithms in modern statistical and probabilistic programming languages such as R or Stan

  • Specify, fit, criticize, and revise Bayesian models in practice

Source: UW Guide 1 UW Guide 2 UW Guide 3

Grade history

↗
average GPA
letter grades
A
AB
B
BC
C
D
F

All recorded terms · compare terms & instructors

Prerequisites

Course map

STAT 609, 610, 611,STAT/​MATH 709,ECON 709,POLI SCI 818, or COMP SCI/​E C E 761

ECON/GENBUS/STAT 775

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

Prerequisite text tree

Professors

Spring 2027

Recent recorded grades — Spring 2024: 4.00 GPA, 100.0% A/AB (n=30 letter grades); Spring 2025: 3.92 GPA, 96.7% A/AB (n=30 letter grades); Spring 2026: 3.88 GPA, 95.0% A/AB (n=20 letter grades).

Historical instructors & teaching patterns

SAMEER DESHPANDE is recorded teaching in Spring 2022, Fall 2022, Spring 2024, Spring 2025, Spring 2026. 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 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 300
LEC 001Classroom Instruction0 / 300
LEC 001Classroom Instruction0 / 300

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records
Download part 1

Student experience

the class

Recent recorded grades — Spring 2024: 4.00 GPA, 100.0% A/AB (n=30 letter grades); Spring 2025: 3.92 GPA, 96.7% A/AB (n=30 letter grades); Spring 2026: 3.88 GPA, 95.0% A/AB (n=20 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Predictive and decision-theoretic motivations including subjective probability, risk, admissibility, and exchangeability
  • Key components of Bayesian analysis (prior, likelihood, posterior, predictive distributions) in parametric, hierarchical, and multilevel models
  • Iterative process of model specification, implementation, criticism, and revision with applied case studies
  • Computational techniques including Markov chain Monte Carlo and variational inference in modern probabilistic programming languages

Skills

  • Justify the use of probability for coherent uncertainty quantification
  • Explain how Bayesian updating occurs in conjugate models and hierarchical models
  • Compare and contrast the conceptual and practical benefits and challenges of different posterior approximation strategies like MCMC and variational inference
  • Implement posterior approximation algorithms in modern statistical and probabilistic programming languages such as R or Stan
  • Specify, fit, criticize, and revise Bayesian models in practice

Grades

Latest available · Spring 2026— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Spring 2026

More grade details Grade mix, volume & source data

Not enough comparable courses for Spring 2027 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.

Download part 1
Selected offering source records
ECON/GENBUS/STAT 775 · Spring 2027

Bayesian Statistics

Recorded 2026-10-14
ECON/GENBUS/STAT 775 · Spring 2027

Bayesian Statistics

Recorded 2026-10-14
ECON/GENBUS/STAT 775 · Spring 2027

Bayesian Statistics

Recorded 2026-10-14
Raw records 
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    "title": "Bayesian Statistics",
    "credits_min": 3,
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Student reviews

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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "b4aff0db3a9017e42cb0a5d45f3c887303a2b20798353dced020519d31b5204b",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
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}