Introduction to Bayesian statistics applied to linguistics

Detalhes bibliográficos
Autor(a) principal: Garcia, Guilherme Duarte
Data de Publicação: 2021
Outros Autores: Lima Jr, Ronaldo Mangueira
Tipo de documento: Artigo
Idioma: por
Título da fonte: Revista da ABRALIN (Online)
Texto Completo: https://revista.abralin.org/index.php/abralin/article/view/1914
Resumo: In this paper, we introduce the basics of Bayesian data analysis and demonstrate how to run a regression model in R using linguistic data. We provide commented code and employ user-friendly packages that optimize the implementation of full-fledged statistical models. Throughout the paper, we compare Bayesian and Frequentist statistics, highlighting the different advantages of a Bayesian approach, which dispenses with the notion of p-values and instead focuses on parameter estimation using posterior distributions of credible effect sizes given the data. We also show how to run a simple model and how to visualize effects of interest. Finally, we suggest additional readings to those interested in Bayesian analysis more generally
id UFPR-12_7f8828fc114fb13315fb9de3d564aa7e
oai_identifier_str oai:ojs.revista.ojs.abralin.org:article/1914
network_acronym_str UFPR-12
network_name_str Revista da ABRALIN (Online)
repository_id_str
spelling Introduction to Bayesian statistics applied to linguisticsIntrodução à estatística bayesiana aplicada à linguísticaAnálise quantitativa de dadosEstatística bayesianaModelos de regressãoQuantitative data analysisBayesian data analysisRegression modelsIn this paper, we introduce the basics of Bayesian data analysis and demonstrate how to run a regression model in R using linguistic data. We provide commented code and employ user-friendly packages that optimize the implementation of full-fledged statistical models. Throughout the paper, we compare Bayesian and Frequentist statistics, highlighting the different advantages of a Bayesian approach, which dispenses with the notion of p-values and instead focuses on parameter estimation using posterior distributions of credible effect sizes given the data. We also show how to run a simple model and how to visualize effects of interest. Finally, we suggest additional readings to those interested in Bayesian analysis more generallyNeste artigo, apresentamos os conceitos fundamentais de uma análise estatística bayesiana e demonstramos como rodar um modelo de regressão utilizando a linguagem R a partir de códigos comentados em detalhe e de pacotes amigáveis que otimizam a implementação de modelos completos. Ao longo do artigo, comparamos estatística bayesiana e estatística frequentista, destacamos as diferentes vantagens apresentadas por uma abordagem bayesiana, que dispensa valores de p e estima distribuições a posteriori de efeitos estatisticamente plausíveis com base nos dados modelados. Por fim, demonstramos como rodar um modelo simples e visualizar efeitos de interesse em gráficos intuitivos. Ao longo do artigo, sugerimos leituras adicionais aos interessados neste tipo de análiseAssociação Brasileira de Linguística2021-12-21info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontextoapplication/pdftext/xmlhttps://revista.abralin.org/index.php/abralin/article/view/191410.25189/rabralin.v20i2.1914Revista da ABRALIN; V. 20, N. 2 (2021); 1-24Revista da ABRALIN; V. 20, N. 2 (2021); 1-240102-715810.25189/rabralin.v20i2reponame:Revista da ABRALIN (Online)instname:Universidade Federal do Paraná (UFPR)instacron:UFPRporhttps://revista.abralin.org/index.php/abralin/article/view/1914/2562https://revista.abralin.org/index.php/abralin/article/view/1914/2564Copyright (c) 2021 Guilherme Duarte Garcia, Ronaldo Mangueira Lima Jrinfo:eu-repo/semantics/openAccessGarcia, Guilherme Duarte Lima Jr, Ronaldo Mangueira 2021-12-21T13:23:33Zoai:ojs.revista.ojs.abralin.org:article/1914Revistahttps://revista.abralin.org/index.php/abralinPUBhttps://revista.abralin.org/index.php/abralin/oairkofreitag@uol.com.br || ra@abralin.org2178-76031678-1805opendoar:2021-12-21T13:23:33Revista da ABRALIN (Online) - Universidade Federal do Paraná (UFPR)false
dc.title.none.fl_str_mv Introduction to Bayesian statistics applied to linguistics
Introdução à estatística bayesiana aplicada à linguística
title Introduction to Bayesian statistics applied to linguistics
spellingShingle Introduction to Bayesian statistics applied to linguistics
Garcia, Guilherme Duarte
Análise quantitativa de dados
Estatística bayesiana
Modelos de regressão
Quantitative data analysis
Bayesian data analysis
Regression models
title_short Introduction to Bayesian statistics applied to linguistics
title_full Introduction to Bayesian statistics applied to linguistics
title_fullStr Introduction to Bayesian statistics applied to linguistics
title_full_unstemmed Introduction to Bayesian statistics applied to linguistics
title_sort Introduction to Bayesian statistics applied to linguistics
author Garcia, Guilherme Duarte
author_facet Garcia, Guilherme Duarte
Lima Jr, Ronaldo Mangueira
author_role author
author2 Lima Jr, Ronaldo Mangueira
author2_role author
dc.contributor.author.fl_str_mv Garcia, Guilherme Duarte
Lima Jr, Ronaldo Mangueira
dc.subject.por.fl_str_mv Análise quantitativa de dados
Estatística bayesiana
Modelos de regressão
Quantitative data analysis
Bayesian data analysis
Regression models
topic Análise quantitativa de dados
Estatística bayesiana
Modelos de regressão
Quantitative data analysis
Bayesian data analysis
Regression models
description In this paper, we introduce the basics of Bayesian data analysis and demonstrate how to run a regression model in R using linguistic data. We provide commented code and employ user-friendly packages that optimize the implementation of full-fledged statistical models. Throughout the paper, we compare Bayesian and Frequentist statistics, highlighting the different advantages of a Bayesian approach, which dispenses with the notion of p-values and instead focuses on parameter estimation using posterior distributions of credible effect sizes given the data. We also show how to run a simple model and how to visualize effects of interest. Finally, we suggest additional readings to those interested in Bayesian analysis more generally
publishDate 2021
dc.date.none.fl_str_mv 2021-12-21
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
texto
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://revista.abralin.org/index.php/abralin/article/view/1914
10.25189/rabralin.v20i2.1914
url https://revista.abralin.org/index.php/abralin/article/view/1914
identifier_str_mv 10.25189/rabralin.v20i2.1914
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://revista.abralin.org/index.php/abralin/article/view/1914/2562
https://revista.abralin.org/index.php/abralin/article/view/1914/2564
dc.rights.driver.fl_str_mv Copyright (c) 2021 Guilherme Duarte Garcia, Ronaldo Mangueira Lima Jr
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 Guilherme Duarte Garcia, Ronaldo Mangueira Lima Jr
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
text/xml
dc.publisher.none.fl_str_mv Associação Brasileira de Linguística
publisher.none.fl_str_mv Associação Brasileira de Linguística
dc.source.none.fl_str_mv Revista da ABRALIN; V. 20, N. 2 (2021); 1-24
Revista da ABRALIN; V. 20, N. 2 (2021); 1-24
0102-7158
10.25189/rabralin.v20i2
reponame:Revista da ABRALIN (Online)
instname:Universidade Federal do Paraná (UFPR)
instacron:UFPR
instname_str Universidade Federal do Paraná (UFPR)
instacron_str UFPR
institution UFPR
reponame_str Revista da ABRALIN (Online)
collection Revista da ABRALIN (Online)
repository.name.fl_str_mv Revista da ABRALIN (Online) - Universidade Federal do Paraná (UFPR)
repository.mail.fl_str_mv rkofreitag@uol.com.br || ra@abralin.org
_version_ 1798329771885592576

Registros relacionados