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 decision making, and applying them to understand performance in the workplace. He takes a Bayesian approach to estimating and testing such models.

Venue

• In person: Future of Work Institute (78 Murray Street Perth WA 6000)

• Online: via WebEx

RSVP

RSVP your attendance to fowi-admin@curtin.edu.au and let us know your preference (in-person or online)

Preparation/Pre-reading:

Dr Strickland has provided R scripts for each demonstration, this will be provided to you upon RSVP. Although the talk can be understood without the scripts, they can be helpful in facilitating comprehension. To run the scripts, R and Rstudio are required, which can be installed . The script 0-packages.R contains the syntax to install necessary R packages and should be run before the presentation. Other scripts can also be run beforehand for preparation, but their relevance will be better understood during the presentation.through the link provided

If you need assistance with R, Rstudio or the scripts, please email luke.strickland@curtin.edu.au