A few statistical principles for data science

DOI10.1111/ANZS.12324zbMath1521.62012arXiv2102.01892OpenAlexW3160349047MaRDI QIDQ6051623

Noel Cressie

Publication date: 20 October 2023

Published in: Australian & New Zealand Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2102.01892

zbMATH Keywords

spatial statisticsmeasurement errorregressionapplied statisticshierarchical statistical models

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Foundations and philosophical topics in statistics (62A01) Statistical aspects of big data and data science (62R07)

Related Items (1)

A Festschrift for Adrian Baddeley

Cites Work

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• Statistical decision theory and Bayesian analysis. 2nd ed
• Removing Nonadditivity from Two-Way Tables with One Observation per Cell
• Combining Incompatible Spatial Data
• Prediction of Spatial Cumulative Distribution Functions Using Subsampling
• Ecological Bias: Use of Maximum-Entropy Approximations
• Mission CO₂ntrol: A Statistical Scientist's Role in Remote Sensing of Atmospheric Carbon Dioxide
• Comment: When Is It Data Science and When Is It Data Engineering?
• Measures of Association for Cross Classifications

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