Description: 

Course participants will learn about multilevel non-linear Bayesian modeling, and how it is applied to study social, linguistic and cognitive phenomena. Advanced Bayesian modeling overcomes many of the limitations of more traditional statistical tools, enabling to performed nuanced direct comparison between different theoretical models, to integrate theoretical evidence, model complex relationships between multiple predictors and outcomes, and to deal with low and incomplete evidence. Course participants will receive introductions to the computational bases of Bayesian modeling and get hands-on experience with it, relying on R, brms and Stan, widely used software packages for statistical modeling.

Dates: June 4-7 2018 (including June 5th!)

REGISTRATION

Time: 9-12 and 13-16

Teacher: Paul Buerkner

Organizer: Riccardo Fusaroli