learnB4SS

LEARN BAYESIAN ANALYSIS FOR SPEECH SCIENCES

Our understanding of human speech is increasingly shaped by quantitative data. It is thus of critical importance to evaluate quantitative findings inferentially. This workshop aims at introducing Bayesian inference for the quantification of phonetic data.

Bayesian inference more closely answers the research questions we ask; it is much more flexible; and it allows us to run appropriate statistical tests.

Until recently, this framework was technically very involved and represented computational challenges. These challenges have now been overcome, making Bayesian inference conceptually, technically, and computationally feasible for researchers across disciplines.

Do you want to learn Bayesian data analysis?You’ve come to the right place

Why Bayesian?

Flexible Modelling

Robust Inference

Technically feasible

The Workshop

5-6th and 12th July 2021.

10am EST — 2pm EST (check your local time here)

Our workshop introduces the logic of Bayesian inference and contrast it to null-hypothesis-significance-testing. After providing a brief conceptual introduction, the course will walk through a Bayesian statistical analysis using R and the package brms (Bürkner 2017).

We will explain how to set up a Bayesian regression model (including setting appropriate priors), how to test 'hypotheses' (including parameter estimation and Bayes factor), how to interpret the results, how to diagnose model convergence, and how to visualize and report the results. In hands-on exercises, the participants will immediately apply their knowledge to new data sets in R.

This workshop is sponsored by the Association for Laboratory Phonology, and is free for members of the ALP. If you would like to participate in this workshop and are not currently an ALP member, please become a member now. Remember to also register for the workshop!

Save the date!

dates

The instructors

  • Team Member

    Timo Roettger

    University of Oslo

    Team Member

    Joseph Casillas

    Rutgers University

    Team Member

    Stefano Coretta

    LMU Munich