The Centre for Advanced Research in Experimental & Applied Linguistics (ARiEAL) at McMaster University in Hamilton, Ontario, is hosting a workshop on Bayesian modelling on the morning of January 15th, 2019.
In recent years, Bayesian inference is gaining increasing popularity. This workshop will serve as a brief introduction to this exciting alternative analytical approach, focusing on do-it-yourself modeling techniques, which allow for maximal flexibility and transparency in data analysis. In a nutshell, such techniques are based on the specification of a generative model that presumably gives rise to the observed data. To do so, one specifies the relevant latent parameters, prior distributions regarding these parameters (reflecting researchers’ a-priori knowledge), and relations between the various parameters as well as between parameters and observed data. Dr. Noam Siegelman (Haskins Labs) will go over basic concepts such as prior and posterior distributions, learn how to specify and interpret graphical models, and practice the implementation of such models using R and JAGS. He will also discuss the difference between Bayesian modeling and Bayesian statistics and the relation between Bayesian parameter estimation and Bayesian model selection via Bayes Factors.
Presenter: Dr. Noam Siegelman
Date: Tuesday, January 15, 2019
Time: 9:30 am to 11:30 am
Location: TSH 203
RSVP: If you are interested, please email firstname.lastname@example.org by Monday, January 14, 2019.
Space is limited. Basic knowledge and experience with R is required. Basic knowledge of Bayesian statistics is recommended, but not required. Please note you will need to bring your own laptop with R installed. Prior to the workshop, please follow the instructions to install JAGS.