Open Access
November 2019 Statistical Theory Powering Data Science
Junhui Cai, Avishai Mandelbaum, Chaitra H. Nagaraja, Haipeng Shen, Linda Zhao
Statist. Sci. 34(4): 669-691 (November 2019). DOI: 10.1214/19-STS754


Statisticians are finding their place in the emerging field of data science. However, many issues considered “new” in data science have long histories in statistics. Examples of using statistical thinking are illustrated, which range from exploratory data analysis to measuring uncertainty to accommodating nonrandom samples. These examples are then applied to service networks, baseball predictions and official statistics.


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Junhui Cai. Avishai Mandelbaum. Chaitra H. Nagaraja. Haipeng Shen. Linda Zhao. "Statistical Theory Powering Data Science." Statist. Sci. 34 (4) 669 - 691, November 2019.


Published: November 2019
First available in Project Euclid: 8 January 2020

zbMATH: 07240222
MathSciNet: MR4048597
Digital Object Identifier: 10.1214/19-STS754

Keywords: decennial census , Empirical Bayes , house price index , nonparametric estimation , Queueing theory , Service networks , sports statistics

Rights: Copyright © 2019 Institute of Mathematical Statistics

Vol.34 • No. 4 • November 2019
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