EMLAR 2022 tutorial on Bayesian methods

This article is originally published at https://vasishth-statistics.blogspot.com/

 At EMLAR 2022 I will teach two sessions that will introduce Bayesian methods. Here is the abstract for the two sessions:

EMLAR 2022: An introduction to Bayesian data analysis

Taught by Shravan Vasishth (vasishth.github.io)

Session 1. 19 April 2022 (Zoom link will be provided)

Modern probabilistic programming languages like Stan (mc-stan.org)

have made Bayesian methods increasingly accessible to researchers

in linguistics and psychology. However, finding an entry point

into these methods is often difficult for researchers. In this

tutorial, I will provide an informal introduction to the

fundamental ideas behind Bayesian statistics, using examples

that illustrate applications to psycholinguistics.

I will also discuss some of the advantages of the Bayesian

approach over the standardly used frequentist paradigms:

uncertainty quantification, robust estimates through regularization,

the ability to incorporate expert and/or prior knowledge into

the data analysis, and the ability to flexibly define the

generative process and thereby to directly address the actual research

question (as opposed to a straw-man null hypothesis).

Suggestions for further reading will be provided. In this tutorial,

I presuppose that the audience is familiar with linear mixed models

(as used in R with the package lme4).

Session 2. 21 April 2022 (Zoom link will be provided)

This session presupposed that the participant has attended

Session 1. I will show some case studies using brms and Stan

code that will demonstrate the major applications of

Bayesian methods in psycholinguistics. I will reference/use some of

the material described in this online textbook (in progress):

https://vasishth.github.io/bayescogsci/book/

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This article is originally published at https://vasishth-statistics.blogspot.com/
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