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Applied Bayesian Statistics

STAT 6350 - Applied Bayesian Statistics: an introduction to theory and methods of the Bayesian approach to statistical inference and data analysis. Covers components of Bayesian analysis (prior, likelihood, posterior), computational algorithms, and philosophical differences among various schools of statistical thought.

Introduction to Bayesian Statistics
Jan 13
Frequentist Inference
Jan 18
Bayesian Inference for the Binomial Model
Jan 25
Bayesian Inference for the Poisson Model
Feb 08
Monte Carlo Sampling
Feb 15
Bayesian Inference for the Normal Model
Feb 22
The Normal Model in a Two Parameter Setting
Mar 15
Metropolis-Hastings Algorithms
Mar 22
Hierarchical Models
Mar 29
Bayesian Linear Regression
Apr 05
Penalized Linear Regression and Model Selection
Apr 12
Bayesian Generalized Linear Models
Apr 19
A Bayesian Perspective on Missing Data Imputation
Apr 26