Computational Statistics and Data Science in the Twenty-first Century

Data science has arrived, and computational statistics is its engine. As the scale and complexity of scientific and industrial data grow, the discipline of computational statistics assumes an increasingly central role among the statistical sciences. An explosion in the range of real-world applicatio...

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Bibliographic Details
Published inarXiv.org
Main Authors Holbrook, Andrew J, Nishimura, Akihiko, Ji, Xiang, Suchard, Marc A
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 12.04.2022
Subjects
Data science
Microprocessors
Quantum computing
Statistics
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Summary:Data science has arrived, and computational statistics is its engine. As the scale and complexity of scientific and industrial data grow, the discipline of computational statistics assumes an increasingly central role among the statistical sciences. An explosion in the range of real-world applications means the development of more and more specialized computational methods, but five Core Challenges remain. We provide a high-level introduction to computational statistics by focusing on its central challenges, present recent model-specific advances and preach the ever-increasing role of non-sequential computational paradigms such as multi-core, many-core and quantum computing. Data science is bringing major changes to computational statistics, and these changes will shape the trajectory of the discipline in the 21st century.
ISSN:2331-8422