The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
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
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