Introduction to Bayesian statistics applied to linguistics
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | |
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 |
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Revista da ABRALIN (Online) |
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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 |