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BAYESIAN STATISTICS

ECON/GENBUS/STAT 775
课程描述

Introduces the theory, methods, and computational procedures needed to perform advanced Bayesian data analyses. Predictive and decision-theoretic motivations including subjective probability, risk, admissibility, and exchangeability; highlights key components of Bayesian analysis (i.e., prior, likelihood, posterior, and predictive distributions) within standard parametric models and advanced hierarchical and multilevel models; demonstrates the iterative process of model specification, implementation, criticism, and revision with applied case studies; implements computational techniques (e.g., Markov chain Monte Carlo, variational inference) in modern probabilistic programming languages.

先修课程
满足要求

This course does not satisfy any prerequisites.

学分

未报告

开课时间

未报告

平均绩点
3.79

5.78% 相比历史数据

完成率
96.77%

-1.61% 相比历史数据

A率
83.87%

28.36% 相比历史数据

班级规模
31

23.42% 相比历史数据

Cumulative Grade Distribution

教师 (2026 Summr)

按评分排序，数据来自 Rate My Professors

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