Overview
Description
Statistical inference using Bayes’ Theorem. Topics include posterior analysis for continuous and discrete random variables, prior specification, Bayesian regression, multivariate inference, and posterior sampling through Markov Chain Monte Carlo.
Requirements
Units
Lecture3
Catalog Details
Offering
Offered: Every Spring
Terms
spring
Attributes
Standard
Learning Outcomes
- demonstrate understanding of the concepts that underlie Bayesian inference and compare the results to frequentist alternatives.
- conduct Bayesian inference analytically and interpret the results.
- perform a Bayesian analysis using professional statistical packages (e.g., Minitab, R, and Stan).