Topic: Introduction to Bayesian Data Analysis

Speaker: Dr. Rong Pan, Arizona State University

Time: 9:00 AM, May 23

Venue: Room 320, Weimin Building

Abstract:

Different from the classical data analysis, the methodology of Bayesian data analysis integrates both information from observed data and from prior knowledge, which can be subjective, to infer a statistical model and to estimate the parameters in the model. In this workshop I will present the basic concepts of Bayesian inference, starting from Bayes’ to likelihood function, prior and posterior distributions. I will compare Bayesian approach to the classical frequentist approach to data analysis and model building process. Examples are drawn from failure time data analysis, where only limited data are collected and prior knowledge can help in making estimation or prediction with less uncertainty.

Biography of the Speaker:

Dr. Rong Pan received his doctorate in industrial engineering from the Pennsylvania State University in 2002. Currently he is an associate professor at the School of Computing, Informatics, and Decision Systems Engineering, Arizona State University. His research interests include quality and reliability engineering, design of experiments, time series analysis, and statistical learning theory.

School of Reliability and Systems Engineering