April 2025
Intermediate to advanced
324 pages
7h 7m
Portuguese (Portugal, Brazil)
Content preview from Pensa em Estatística, 3ª Edição
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Capítulo 14. Métodos analíticos
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Este livro centrou-se em métodos computacionais como a simulação e a reamostragem, mas alguns dos problemas que resolvemos têm soluções analíticas que podem ser muito mais rápidas de calcular.
Este capítulo apresenta alguns destes métodos e explica o seu funcionamento. No final do capítulo, apresenta sugestões para a integração de métodos computacionais e analíticos na análise de dados.
Gráficos de probabilidade normal
Muitos métodos analíticos baseiam-se nas propriedades da distribuição normal, por duas razões: as distribuições de muitas medidas no mundo real são bem aproximadas por distribuições normais e as distribuições normais têm propriedades matemáticas que as tornam úteis para análise.
Para demonstrar o primeiro ponto, vamos analisar algumas das medições no conjunto de dados dos pinguins. Depois, explora as propriedades matemáticas da distribuição normal. As instruções para descarregar os dados estão no bloco de notas deste capítulo.
Podemos ler os dados da seguinte forma:
penguins=pd.read_csv("penguins_raw.csv")penguins.shape
(344, 17)
O conjunto de dados contém medições de três espécies de pinguins. Para este exemplo, seleccionaremos os pinguins Adélie:
adelie=penguins.query('Species.str.startswith("Adelie")').copy()len(adelie)
152
Para ver se os pesos dos pinguins seguem uma distribuição normal, calcula a CDF ...
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