Testes Monte Carlo para autovalores na verificação de consenso multivariado de painéis sensoriais

Detalhes bibliográficos
Ano de defesa: 2019
Autor(a) principal: Araujo, Tatiane Gomes De lattes
Orientador(a): Ferreira, Eric Batista lattes
Banca de defesa: Lúcia, Flávia Della, Dias, Adriana
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Alfenas
Programa de Pós-Graduação: Programa de Pós-Graduação em Estatística Aplicada e Biometria
Departamento: Instituto de Ciências Exatas
País: Brasil
Palavras-chave em Português:
Área do conhecimento CNPq:
Link de acesso: https://repositorio.unifal-mg.edu.br/handle/123456789/1392
Resumo: In sensory analysis, the concordance between the members of a panel is fundamental to verify the efficiency of the training received by it. To this purpose, some methods and tests are found in the literature, among which are the asymptotic tests of Ferreira (2017), which evaluate the consonance of a panel in a multivariate form. Because they are asymptotic tests, they require a large number of sample observations, which is not common in the sensory context. Therefore, the objective of this work was to propose Monte Carlo versions of the Ferreira tests (2017) to obtain better characteristics of power and type I error in any sample size, as well as to compare them with the asymptotic tests via computerized simulation. It was also an objective to adapt the panel performance verification protocol proposed by Tomic et al. (2009), inserting a multivariate consensus test step. The four Monte Carlo tests proposed were considered accurate and presented higher power in 95,24% of the analyzed scenarios, when compared with the asymptotic versions. The use of the InvH2mc test is recommended. The efficiency of this test could be proven by verifying the performance of a sensory panel when evaluating two brands of guarana soda flavor in both their traditional and zero sugar versions. It was found that the panel did not present a multivariate consensus, that is, the tasters did not score the attributes similarly. The insertion of the Monte Carlo test in the protocol allowed inferential analysis of the panel’s behavior, corroborating the exploratory phases.
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spelling Araujo, Tatiane Gomes Dehttp://lattes.cnpq.br/9965398009651936Lúcia, Flávia DellaDias, AdrianaFerreira, Eric Batistahttp://lattes.cnpq.br/91930537707236882019-06-18T17:27:28Z2019-02-27ARAUJO, Tatiane Gomes de. Testes Monte Carlo para autovalores na verificação de consenso multivariado de painéis sensoriais. 2019. 86 f. Dissertação (Dissertação em Estatística Aplicada e Biometria) - Universidade Federal de Alfenas, Alfenas, MG, 2019.https://repositorio.unifal-mg.edu.br/handle/123456789/1392In sensory analysis, the concordance between the members of a panel is fundamental to verify the efficiency of the training received by it. To this purpose, some methods and tests are found in the literature, among which are the asymptotic tests of Ferreira (2017), which evaluate the consonance of a panel in a multivariate form. Because they are asymptotic tests, they require a large number of sample observations, which is not common in the sensory context. Therefore, the objective of this work was to propose Monte Carlo versions of the Ferreira tests (2017) to obtain better characteristics of power and type I error in any sample size, as well as to compare them with the asymptotic tests via computerized simulation. It was also an objective to adapt the panel performance verification protocol proposed by Tomic et al. (2009), inserting a multivariate consensus test step. The four Monte Carlo tests proposed were considered accurate and presented higher power in 95,24% of the analyzed scenarios, when compared with the asymptotic versions. The use of the InvH2mc test is recommended. The efficiency of this test could be proven by verifying the performance of a sensory panel when evaluating two brands of guarana soda flavor in both their traditional and zero sugar versions. It was found that the panel did not present a multivariate consensus, that is, the tasters did not score the attributes similarly. The insertion of the Monte Carlo test in the protocol allowed inferential analysis of the panel’s behavior, corroborating the exploratory phases.Em análise sensorial a concordância entre os membros de um painel é fundamental para verificar a eficiência do treinamento por ele recebido. Para essa finalidade, encontram-se na literatura alguns métodos e testes, dentre os quais destacam-se os testes assintóticos de Ferreira (2017), que avaliam a consonância de um painel de forma multivariada. Por serem testes assintóticos, eles necessitam de um grande número de observações amostrais, o que não é comum no contexto sensorial. Diante disso, o objetivo deste trabalho foi propor versões Monte Carlo dos testes de Ferreira (2017) para obter melhores características de poder e erro tipo I em qualquer tamanho amostral, bem como compará-los com os testes assintóticos via simulação computacional. Também foi objetivo, adaptar o protocolo de verificação de desempenho de painéis proposto por Tomic et al. (2009), inserindo uma etapa de teste de consenso multivariado. Os quatro testes Monte Carlo propostos foram considerados exatos e apresentaram maior poder em 95,24% dos cenários analisados, quando comparados com as versões assintóticas. Recomenda-se o uso do teste InvH2mc. A eficiência deste teste pôde ser comprovada ao verificar o desempenho de um painel sensorial ao avaliar duas marcas de refrigerante sabor guaraná em suas versões tradicionais e zero açúcar. Verificou-se que o painel não apresentou consenso multivariado, ou seja, os provadores não pontuaram os atributos de forma semelhante. A inserção do teste Monte Carlo no protocolo permitiu analisar de forma inferencial o comportamento do painel, corroborando com as fases exploratórias.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESapplication/pdfporUniversidade Federal de AlfenasPrograma de Pós-Graduação em Estatística Aplicada e BiometriaUNIFAL-MGBrasilInstituto de Ciências Exatasinfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/4.0/SensometriaConcordância de painéisTeste Monte CArloPROBABILIDADE E ESTATISTICA::PROBABILIDADE E ESTATISTICA APLICADASTestes Monte Carlo para autovalores na verificação de consenso multivariado de painéis sensoriaisinfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/publishedVersion-8156311678363143599600600600-21048508539903632002075167498588264571reponame:Biblioteca Digital de Teses e Dissertações da UNIFALinstname:Universidade Federal de Alfenas (UNIFAL)instacron:UNIFALAraujo, Tatiane Gomes DeLICENSElicense.txtlicense.txttext/plain; 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dc.title.pt-BR.fl_str_mv Testes Monte Carlo para autovalores na verificação de consenso multivariado de painéis sensoriais
title Testes Monte Carlo para autovalores na verificação de consenso multivariado de painéis sensoriais
spellingShingle Testes Monte Carlo para autovalores na verificação de consenso multivariado de painéis sensoriais
Araujo, Tatiane Gomes De
Sensometria
Concordância de painéis
Teste Monte CArlo
PROBABILIDADE E ESTATISTICA::PROBABILIDADE E ESTATISTICA APLICADAS
title_short Testes Monte Carlo para autovalores na verificação de consenso multivariado de painéis sensoriais
title_full Testes Monte Carlo para autovalores na verificação de consenso multivariado de painéis sensoriais
title_fullStr Testes Monte Carlo para autovalores na verificação de consenso multivariado de painéis sensoriais
title_full_unstemmed Testes Monte Carlo para autovalores na verificação de consenso multivariado de painéis sensoriais
title_sort Testes Monte Carlo para autovalores na verificação de consenso multivariado de painéis sensoriais
author Araujo, Tatiane Gomes De
author_facet Araujo, Tatiane Gomes De
author_role author
dc.contributor.author.fl_str_mv Araujo, Tatiane Gomes De
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/9965398009651936
dc.contributor.referee1.fl_str_mv Lúcia, Flávia Della
dc.contributor.referee2.fl_str_mv Dias, Adriana
dc.contributor.advisor1.fl_str_mv Ferreira, Eric Batista
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/9193053770723688
contributor_str_mv Lúcia, Flávia Della
Dias, Adriana
Ferreira, Eric Batista
dc.subject.por.fl_str_mv Sensometria
Concordância de painéis
Teste Monte CArlo
topic Sensometria
Concordância de painéis
Teste Monte CArlo
PROBABILIDADE E ESTATISTICA::PROBABILIDADE E ESTATISTICA APLICADAS
dc.subject.cnpq.fl_str_mv PROBABILIDADE E ESTATISTICA::PROBABILIDADE E ESTATISTICA APLICADAS
description In sensory analysis, the concordance between the members of a panel is fundamental to verify the efficiency of the training received by it. To this purpose, some methods and tests are found in the literature, among which are the asymptotic tests of Ferreira (2017), which evaluate the consonance of a panel in a multivariate form. Because they are asymptotic tests, they require a large number of sample observations, which is not common in the sensory context. Therefore, the objective of this work was to propose Monte Carlo versions of the Ferreira tests (2017) to obtain better characteristics of power and type I error in any sample size, as well as to compare them with the asymptotic tests via computerized simulation. It was also an objective to adapt the panel performance verification protocol proposed by Tomic et al. (2009), inserting a multivariate consensus test step. The four Monte Carlo tests proposed were considered accurate and presented higher power in 95,24% of the analyzed scenarios, when compared with the asymptotic versions. The use of the InvH2mc test is recommended. The efficiency of this test could be proven by verifying the performance of a sensory panel when evaluating two brands of guarana soda flavor in both their traditional and zero sugar versions. It was found that the panel did not present a multivariate consensus, that is, the tasters did not score the attributes similarly. The insertion of the Monte Carlo test in the protocol allowed inferential analysis of the panel’s behavior, corroborating the exploratory phases.
publishDate 2019
dc.date.accessioned.fl_str_mv 2019-06-18T17:27:28Z
dc.date.issued.fl_str_mv 2019-02-27
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
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dc.identifier.citation.fl_str_mv ARAUJO, Tatiane Gomes de. Testes Monte Carlo para autovalores na verificação de consenso multivariado de painéis sensoriais. 2019. 86 f. Dissertação (Dissertação em Estatística Aplicada e Biometria) - Universidade Federal de Alfenas, Alfenas, MG, 2019.
dc.identifier.uri.fl_str_mv https://repositorio.unifal-mg.edu.br/handle/123456789/1392
identifier_str_mv ARAUJO, Tatiane Gomes de. Testes Monte Carlo para autovalores na verificação de consenso multivariado de painéis sensoriais. 2019. 86 f. Dissertação (Dissertação em Estatística Aplicada e Biometria) - Universidade Federal de Alfenas, Alfenas, MG, 2019.
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