Applied Bayesian Regression Analysis

Session Submission Type: Workshop

Description

This workshop introduces Bayesian analysis by comparing it with the traditional frequentist inference under the general regression framework. The discussion will focus on the conceptual ideas of Bayesian and frequentist estimations, their applications with classical generalized regression models, and easy interpretation of results using R and Stan.

This workshop plans to cover the following sub-topics,
1. Thomas Bayes, Bayes’s Theorem, and Bayesian Inference
2. Classical Linear Regression Models
3. Bayesian Analysis of Linear Regression Models
4. Bayesian Analysis of Binary Regression Models
5. Advanced Regression Models

The learning objectives that I plan to accomplish after my workshop include,
1. Participants understand the conceptual ideas behind Bayesian estimation and inference
2. Participants can run simple Bayesian regression models with R
3. Participants can interpret the results, especially those from Bayesian analysis with R and Stan
4. Participants understand the difference between Bayesian and frequentist methods
5. Participants know the resources for continuing education on this topic

Sub Unit

• Workshops / Professional Development Workshop

Presenter

• Jun Xu, University of Macau

Session Organizer

• Jun Xu, University of Macau