Cited by 1,192Statistical Methods and ApplicationsStatistical and numerical algorithmsStatistical Methods and Bayesian Inference

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Statistical Data Analysis in the Computer Age

Efron, Bradley, Tibshirani, Robert·1991·Science

DOI 10.1126/science.253.5018.390

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Abstract

Most of our familiar statistical methods, such as hypothesis testing, linear regression, analysis of variance, and maximum likelihood estimation, were designed to be implemented on mechanical calculators. Modern electronic computation has encouraged a host of new statistical methods that require fewer distributional assumptions than their predecessors and can be applied to more complicated statistical estimators. These methods allow the scientist to explore and describe data and draw valid statistical inferences without the usual concerns for mathematical tractability. This is possible because traditional methods of mathematical analysis are replaced by specially constructed computer algorithms. Mathematics has not disappeared from statistical theory. It is the main method for deciding which algorithms are correct and efficient tools for automating statistical inference.

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Crossref · 10.1126/science.253.5018.390

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Authors: Efron, B., & Tibshirani, R.
Affiliations: Stanford University (US)
University of Toronto (CA)
ORCID: Tibshirani, Robert
Venue: Science
Publisher: American Association for the Advancement of Science (AAAS)
Published: 1991-07-26
Volume: 253
Issue: 5018
Pages: 390-395
ISSN: 0036-8075 (ISSN-L)
1095-9203
DOI: 10.1126/science.253.5018.390
OpenAlex: W2045925085
Cited by: 1,192
References: 11
Citations by year: 2026: 14 · 2025: 24 · 2024: 34 · 2023: 24 · 2022: 30 · 2021: 29 · 2020: 39 · 2019: 24 · 2018: 35 · 2017: 44 · 2016: 25 · 2015: 30 · 2014: 28 · 2013: 43 · 2012: 48
FWCI: 49.38
Type: journal article
Language: en
Open access: closed
Locations: Science (publishedVersion)
PubMed (publishedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Keywords: statistical inference, hypothesis testing, linear regression, analysis of variance, maximum likelihood estimation, distributional assumptions, statistical software, statistical computing

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