Data Science in a Time of Crisis: Lessons from the Pandemic-Reference-Cited by-同舟云学术

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Data Science in a Time of Crisis: Lessons from the Pandemic

Published:2022-05-01 Issue:2 Volume:37 Page:
ISSN:0883-4237
Container-title:Statistical Science
language:
Short-container-title:Statist. Sci.

Author:

Sabatti Chiara¹,Chambers John M.²

Affiliation:

1. Chiara Sabatti is Professor, Biomedical Data Science and of Statistics, Stanford University, Stanford, California 94305-2070, USA

2. John M. Chambers is Adjunct Professor in Statistics and Senior Advisor, Data Science, Stanford University, Stanford, California 94305-2070, USA

Publisher

Institute of Mathematical Statistics

Subject

Statistics, Probability and Uncertainty,General Mathematics,Statistics and Probability

Reference9 articles.

1. CAPPELLO, L., KIM, J., LIU, S. and PALACIOS, J. A. (2022). Statistical challenges in tracking the evolution of SARS-CoV-2. Statist. Sci. 37 162–182.

2. CHAMBERS, J. M. (2022). Data, science, and global disasters. Statist. Sci. 37 284–288.

3. COMESS, S., WANG, H., HOLMES, S. and DONNAT, C. (2022). Statistical modeling for practical pooled testing during the COVID-19 pandemic. Statist. Sci. 37 229–250.

4. JAHJA, M., CHIN, A. and TIBSHIRANI, R. J. (2022). Real-time estimation of COVID-19 infections: Deconvolution and sensor fusion. Statist. Sci. 37 207–228.

5. LIN, X. (2022). Lessons learned from the COVID-19 pandemic: A statistician’s reflection. Statist. Sci. 37 278–283.

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The importance of investing in data, models, experiments, team science, and public trust to help policymakers prepare for the next pandemic;PLOS Global Public Health;2023-11-30

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