Explorando os modelos de estudantes sobre amostragem e inferência com variáveis nominais
DOI:
https://doi.org/10.48489/quadrante.23655Palavras-chave:
variáveis categóricas, suscitar as ideias dos alunos, perspetiva de modelos e modelação, categorias nominais, formação inicial de professores, amostragemResumo
Fazer inferências sobre populações desconhecidas é fundamental no raciocínio estatístico. No entanto, pouca atenção tem sido dada às investigações empíricas sobre como e com que objetivo os alunos desenvolvem modelos de amostragem ao investigarem uma variável categórica cujos valores são nominais. Tendo por base a perspetiva de modelos e modelação, este artigo relata uma intervenção, durante a qual 25 professores em formação inicial foram solicitados a desenvolver um modelo de amostragem que pudesse ser usado para fazer inferências sobre o número de contas de cores diferentes e sobre a distribuição de contas de cores diferentes em populações de tamanhos diferentes. Por meio de uma análise temática, foram identificados três resultados principais sobre as características dos modelos dos estudantes acerca de amostragem e inferência com variáveis nominais: capturar todas as cores de baixa frequência na população; não sobrevalorizar as cores de baixa frequência na população; e formalizar as relações encontradas para fazer inferências. Os resultados põem em evidência várias questões sobre a compreensão dos alunos acerca da relação entre a representatividade da amostra e a variabilidade da amostra e suas consequências na produção de inferências.
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