Introduction to Bayesian Inference | FOWI Academy

Part of the Future of Work Institute (FOWI) Academy Series

Bayesian inference is increasingly popular in the social sciences. It provides an intuitive framework to reason about uncertainty in models and parameters. Furthermore, Bayesian methods improve the viability of complex approaches such as dynamic structural equation models and cognitive models of decision making. This talk aims to provide a gentle introduction to Bayesian inference for interested social scientists. After discussing advantages of the Bayesian approach, the talk covers fundamentals including Bayes’ rule, Bayesian inference, and parameter estimation with Markov Chain Monte Carlo methods. The expected outcome is an understanding of Bayesian inference fundamentals that can generalize to a wide range of settings.

About the Speaker

Dr Luke Strickland is a Post-Doctoral Fellow at the Curtin Future of Work Institute. His research spans cognitive science, human factors, and quantitative methods. He has a particular interest in building process models of human…