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Statistical literacy is the ability to understand and reason with statistics and data. The abilities to understand and reason with data, or arguments that use data, are necessary for citizens to understand material presented in publications such as newspapers, television, and the Internet. However, scientists also need to develop statistical literacy so that they can both produce rigorous and reproducible research and consume it. Numeracy is an element of being statistically literate and in some models of statistical literacy, or for some populations (e.g., students in kindergarten through 12th grade/end of secondary school), it is a prerequisite skill. Being statistically literate is sometimes taken to include having the abilities to both critically evaluate statistical material and appre

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  • Statistical literacy (en)
  • Literacia estatística (pt)
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  • Statistical literacy is the ability to understand and reason with statistics and data. The abilities to understand and reason with data, or arguments that use data, are necessary for citizens to understand material presented in publications such as newspapers, television, and the Internet. However, scientists also need to develop statistical literacy so that they can both produce rigorous and reproducible research and consume it. Numeracy is an element of being statistically literate and in some models of statistical literacy, or for some populations (e.g., students in kindergarten through 12th grade/end of secondary school), it is a prerequisite skill. Being statistically literate is sometimes taken to include having the abilities to both critically evaluate statistical material and appre (en)
  • Alfabetização estatística ou Literacia estatística, são termos utilizados a fim de descrever a habilidade individual para compreender estatísticas. Essa aptidão é considerada essencial para que os cidadãos compreendam o conteúdo publicado nos jornais, na televisão e na Internet. Nesse sentido, a numeracia é um pré-requisito para ser estatisticamente literado. (pt)
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  • Statistical literacy is the ability to understand and reason with statistics and data. The abilities to understand and reason with data, or arguments that use data, are necessary for citizens to understand material presented in publications such as newspapers, television, and the Internet. However, scientists also need to develop statistical literacy so that they can both produce rigorous and reproducible research and consume it. Numeracy is an element of being statistically literate and in some models of statistical literacy, or for some populations (e.g., students in kindergarten through 12th grade/end of secondary school), it is a prerequisite skill. Being statistically literate is sometimes taken to include having the abilities to both critically evaluate statistical material and appreciate the relevance of statistically-based approaches to all aspects of life in general or to the evaluating, design, and/or production of scientific work. (en)
  • Alfabetização estatística ou Literacia estatística, são termos utilizados a fim de descrever a habilidade individual para compreender estatísticas. Essa aptidão é considerada essencial para que os cidadãos compreendam o conteúdo publicado nos jornais, na televisão e na Internet. Nesse sentido, a numeracia é um pré-requisito para ser estatisticamente literado. Atualmente, as pessoas são inundadas com informações estatísticas em anúncios, notícias ou conversas em geral. Além disso, especialistas frequentemente utilizam números para construir seus argumentos, o que torna a Literacia estatística uma faculdade necessária ao discernimento acerca da veracidade das alegações. Essa análise é importante porque as estatísticas podem ser utilizadas para produzir inverdades e/ou representações menos claras da realidade, mas utilizando dados que podem ser válidos. O objetivo da Literacia estatística é, então, melhorar a compreensão pública dos dados estatísticos. Ainda que os resultados das pesquisas de opinião sejam constantemente citados por diversas organizações, sua qualidade é consideravelmente variada. Por isso, alguma compreensão das técnicas de amostragem é necessária para que haja uma correta interpretação dos resultados, pois, por exemplo, a amostra pode ser tendenciosa ou seu tamanho pode ser pequeno para desenvolver conclusões significativas. (pt)
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