{"title":"Statistics education on the sly: exploring large scientific data sets as an entrée to statistical ideas in secondary schools","authors":"J. Hammerman","doi":"10.52041/srap.09802","DOIUrl":null,"url":null,"abstract":"Many large scientific and social scientific data sets—for example, those about climate and the environment, medicine, population or economic trends, the human genome, astronomy— are now widely available. As secondary students explore these data they investigate fascinating and important topics that can help them better participate as global citizens. However, understanding the meaning of these data requires statistical understandings—e.g., of variability amidst underlying aggregate trends, statistical control in complex relationships, the meaning of interaction effects, expectations about small probability events, statistical versus practical significance—that are difficult and rarely taught at the secondary level. This paper explores how interest in the science can motivate exploration of statistical ideas, at an informal if not rigorous technical level, which in turn can lead to a deeper understanding of scientific ideas. The role of data visualization and analysis tools to support this learning is also explored.","PeriodicalId":170012,"journal":{"name":"Next Steps in Statistics Education Precedings IASE Satellite Conference","volume":"129 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Next Steps in Statistics Education Precedings IASE Satellite Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52041/srap.09802","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Many large scientific and social scientific data sets—for example, those about climate and the environment, medicine, population or economic trends, the human genome, astronomy— are now widely available. As secondary students explore these data they investigate fascinating and important topics that can help them better participate as global citizens. However, understanding the meaning of these data requires statistical understandings—e.g., of variability amidst underlying aggregate trends, statistical control in complex relationships, the meaning of interaction effects, expectations about small probability events, statistical versus practical significance—that are difficult and rarely taught at the secondary level. This paper explores how interest in the science can motivate exploration of statistical ideas, at an informal if not rigorous technical level, which in turn can lead to a deeper understanding of scientific ideas. The role of data visualization and analysis tools to support this learning is also explored.