Toward the Applicability of Statistics: A Representational View

Detalhes bibliográficos
Autor(a) principal: Ashoori, Mahdi
Data de Publicação: 2019
Outros Autores: Taheri, S. Mahmoud
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Principia (Florianópolis. Online)
Texto Completo: https://periodicos.ufsc.br/index.php/principia/article/view/1808-1711.2019v23n1p113
Resumo: The problem of understanding how statistical inference is, and can be, applied in  empirical sciences is important for the methodology of science. It is the objective of this paper  to gain a better understanding of the role of statistical methods in scientific modeling. The  important question of whether the applicability reduces to the representational properties  of statistical models is discussed. It will be shown that while the answer to this question  is positive, representation in statistical models is not purely structural. In spite of the fact  that representation in statistical models is based on the structural similarities between the  statistical model and the empirical systems under study, these relationships are shown to be  appropriate for representing relations in the target system by agent function, too. A second  aspect of the paper involves the claim that agent-based components of statistical modeling  are: a) interpretation of random variables, b) selection of the goal of statistical research, and  c) selection of estimator properties. To justify these claims, a preliminary discussion will be  presented on the role of statistics in modeling, as in regression and other structural models.  This role will be explored and realized using a structural viewpoint. Also the role of statistical  estimation in statistical modeling is discussed to explain the representational role of models  and the inferential role of the agent in modeling. 
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spelling Toward the Applicability of Statistics: A Representational ViewToward the Applicability of Statistics: A Representational ViewThe problem of understanding how statistical inference is, and can be, applied in  empirical sciences is important for the methodology of science. It is the objective of this paper  to gain a better understanding of the role of statistical methods in scientific modeling. The  important question of whether the applicability reduces to the representational properties  of statistical models is discussed. It will be shown that while the answer to this question  is positive, representation in statistical models is not purely structural. In spite of the fact  that representation in statistical models is based on the structural similarities between the  statistical model and the empirical systems under study, these relationships are shown to be  appropriate for representing relations in the target system by agent function, too. A second  aspect of the paper involves the claim that agent-based components of statistical modeling  are: a) interpretation of random variables, b) selection of the goal of statistical research, and  c) selection of estimator properties. To justify these claims, a preliminary discussion will be  presented on the role of statistics in modeling, as in regression and other structural models.  This role will be explored and realized using a structural viewpoint. Also the role of statistical  estimation in statistical modeling is discussed to explain the representational role of models  and the inferential role of the agent in modeling. The problem of understanding how statistical inference is, and can be, applied in  empirical sciences is important for the methodology of science. It is the objective of this paper  to gain a better understanding of the role of statistical methods in scientific modeling. The  important question of whether the applicability reduces to the representational properties  of statistical models is discussed. It will be shown that while the answer to this question  is positive, representation in statistical models is not purely structural. In spite of the fact  that representation in statistical models is based on the structural similarities between the  statistical model and the empirical systems under study, these relationships are shown to be  appropriate for representing relations in the target system by agent function, too. A second  aspect of the paper involves the claim that agent-based components of statistical modeling  are: a) interpretation of random variables, b) selection of the goal of statistical research, and  c) selection of estimator properties. To justify these claims, a preliminary discussion will be  presented on the role of statistics in modeling, as in regression and other structural models.  This role will be explored and realized using a structural viewpoint. Also the role of statistical  estimation in statistical modeling is discussed to explain the representational role of models  and the inferential role of the agent in modeling. Federal University of Santa Catarina – UFSC2019-04-26info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufsc.br/index.php/principia/article/view/1808-1711.2019v23n1p11310.5007/1808-1711.2019v23n1p113Principia: an international journal of epistemology; Vol. 23 No. 1 (2019); 113-129Principia: an international journal of epistemology; Vol. 23 Núm. 1 (2019); 113-129Principia: an international journal of epistemology; v. 23 n. 1 (2019); 113-1291808-17111414-4247reponame:Principia (Florianópolis. Online)instname:Universidade Federal de Santa Catarina (UFSC)instacron:UFSCenghttps://periodicos.ufsc.br/index.php/principia/article/view/1808-1711.2019v23n1p113/pdfCopyright (c) 2021 Mahdi Ashoori, S. Mahmoud Taheriinfo:eu-repo/semantics/openAccessAshoori, MahdiTaheri, S. Mahmoud2019-12-16T14:31:11Zoai:periodicos.ufsc.br:article/50386Revistahttps://periodicos.ufsc.br/index.php/principiaPUBhttps://periodicos.ufsc.br/index.php/principia/oaiprincipia@contato.ufsc.br||principia@contato.ufsc.br1808-17111414-4247opendoar:2019-12-16T14:31:11Principia (Florianópolis. Online) - Universidade Federal de Santa Catarina (UFSC)false
dc.title.none.fl_str_mv Toward the Applicability of Statistics: A Representational View
Toward the Applicability of Statistics: A Representational View
title Toward the Applicability of Statistics: A Representational View
spellingShingle Toward the Applicability of Statistics: A Representational View
Ashoori, Mahdi
title_short Toward the Applicability of Statistics: A Representational View
title_full Toward the Applicability of Statistics: A Representational View
title_fullStr Toward the Applicability of Statistics: A Representational View
title_full_unstemmed Toward the Applicability of Statistics: A Representational View
title_sort Toward the Applicability of Statistics: A Representational View
author Ashoori, Mahdi
author_facet Ashoori, Mahdi
Taheri, S. Mahmoud
author_role author
author2 Taheri, S. Mahmoud
author2_role author
dc.contributor.author.fl_str_mv Ashoori, Mahdi
Taheri, S. Mahmoud
description The problem of understanding how statistical inference is, and can be, applied in  empirical sciences is important for the methodology of science. It is the objective of this paper  to gain a better understanding of the role of statistical methods in scientific modeling. The  important question of whether the applicability reduces to the representational properties  of statistical models is discussed. It will be shown that while the answer to this question  is positive, representation in statistical models is not purely structural. In spite of the fact  that representation in statistical models is based on the structural similarities between the  statistical model and the empirical systems under study, these relationships are shown to be  appropriate for representing relations in the target system by agent function, too. A second  aspect of the paper involves the claim that agent-based components of statistical modeling  are: a) interpretation of random variables, b) selection of the goal of statistical research, and  c) selection of estimator properties. To justify these claims, a preliminary discussion will be  presented on the role of statistics in modeling, as in regression and other structural models.  This role will be explored and realized using a structural viewpoint. Also the role of statistical  estimation in statistical modeling is discussed to explain the representational role of models  and the inferential role of the agent in modeling. 
publishDate 2019
dc.date.none.fl_str_mv 2019-04-26
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.ufsc.br/index.php/principia/article/view/1808-1711.2019v23n1p113
10.5007/1808-1711.2019v23n1p113
url https://periodicos.ufsc.br/index.php/principia/article/view/1808-1711.2019v23n1p113
identifier_str_mv 10.5007/1808-1711.2019v23n1p113
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.ufsc.br/index.php/principia/article/view/1808-1711.2019v23n1p113/pdf
dc.rights.driver.fl_str_mv Copyright (c) 2021 Mahdi Ashoori, S. Mahmoud Taheri
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 Mahdi Ashoori, S. Mahmoud Taheri
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Federal University of Santa Catarina – UFSC
publisher.none.fl_str_mv Federal University of Santa Catarina – UFSC
dc.source.none.fl_str_mv Principia: an international journal of epistemology; Vol. 23 No. 1 (2019); 113-129
Principia: an international journal of epistemology; Vol. 23 Núm. 1 (2019); 113-129
Principia: an international journal of epistemology; v. 23 n. 1 (2019); 113-129
1808-1711
1414-4247
reponame:Principia (Florianópolis. Online)
instname:Universidade Federal de Santa Catarina (UFSC)
instacron:UFSC
instname_str Universidade Federal de Santa Catarina (UFSC)
instacron_str UFSC
institution UFSC
reponame_str Principia (Florianópolis. Online)
collection Principia (Florianópolis. Online)
repository.name.fl_str_mv Principia (Florianópolis. Online) - Universidade Federal de Santa Catarina (UFSC)
repository.mail.fl_str_mv principia@contato.ufsc.br||principia@contato.ufsc.br
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