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Data science, big data and statistics
TEST ( IF 1.3 ) Pub Date : 2019-04-08 , DOI: 10.1007/s11749-019-00651-9
Pedro Galeano , Daniel Peña

This article analyzes how Big Data is changing the way we learn from observations. We describe the changes in statistical methods in seven areas that have been shaped by the Big Data-rich environment: the emergence of new sources of information; visualization in high dimensions; multiple testing problems; analysis of heterogeneity; automatic model selection; estimation methods for sparse models; and merging network information with statistical models. Next, we compare the statistical approach with those in computer science and machine learning and argue that the convergence of different methodologies for data analysis will be the core of the new field of data science. Then, we present two examples of Big Data analysis in which several new tools discussed previously are applied, as using network information or combining different sources of data. Finally, the article concludes with some final remarks.

中文翻译:

数据科学,大数据和统计

本文分析了大数据如何改变我们从观察中学习的方式。我们描述了由大数据丰富的环境所塑造的七个领域中统计方法的变化:新信息源的出现;高度可视化;多个测试问题;异质性分析;自动选型 稀疏模型的估计方法;并将网络信息与统计模型合并。接下来,我们将统计方法与计算机科学和机器学习中的统计方法进行比较,并认为数据分析的不同方法的融合将成为数据科学新领域的核心。然后,我们提供两个大数据分析示例,其中使用了先前讨论的几种新工具,例如使用网络信息或组合不同的数据源。
更新日期:2019-04-08
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