Bayesian regression modeling for language data: a crash course

Presenters: Morgan Sonderegger

T1TFE1

This workshop will cover Bayesian regression modeling from foundational concepts to hierarchical Bayesian models (e.g. "mixed-effects models"), using R and Stan/brms. Prior familiarity with R and (frequentist) statistical analysis, ideally up to mixed-effects modeling, is assumed. We will move quickly, using both theoretical background reading and extensive practical exercises using linguistic data, in a "flipped" format that accommodates participants at different levels.

Keywords: Bayesian Inference, R, Statistics

Presenters

Morgan Sonderegger

McGill University

Morgan Sonderegger is Associate Professor of Linguistics at McGill University and Canada Research Chair in Speech Variability. His research focuses on phonetics, sound change, and phonology, primarily using corpus data. Another focus is methodology for quantitative linguistic data: both statistical analysis (e.g. "Regression Modeling for Linguistic Data": MIT Press, 2023) and software for speech database management and automated speech analysis (Montreal Forced Aligner, PolyglotDB, AutoVOT).