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Statistical Data Analysis in the Computer Age
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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“A bootstrap method analogous to a 2-tailed paired t-test was used to assess pre- to post-intervention changes, as some datasets were too small to reasonably verify normality”
From Multi-family pediatric pain group therapy: Capturing acceptance and cultivating change (2017) · cites this paper as [33]
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Metadata
- Authors
- Efron, B., & Tibshirani, R.
- Affiliations
- Stanford University (US)
- University of Toronto (CA)
- ORCID
- Tibshirani, Robert
- Venue
- Science
- Published
- 1991-07-26
- Volume
- 253
- Issue
- 5018
- Pages
- 390-395
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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