- Statist. Sci.
- Volume 34, Number 4 (2019), 669-691.
Statistical Theory Powering Data Science
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.
Statist. Sci., Volume 34, Number 4 (2019), 669-691.
First available in Project Euclid: 8 January 2020
Permanent link to this document
Digital Object Identifier
Mathematical Reviews number (MathSciNet)
Zentralblatt MATH identifier
Cai, Junhui; Mandelbaum, Avishai; Nagaraja, Chaitra H.; Shen, Haipeng; Zhao, Linda. Statistical Theory Powering Data Science. Statist. Sci. 34 (2019), no. 4, 669--691. doi:10.1214/19-STS754. https://projecteuclid.org/euclid.ss/1578474031