Explorations in statistics: the bootstrap
Abstract
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This fourth installment of Explorations in Statistics explores the bootstrap. The bootstrap gives us an empirical approach to estimate the theoretical variability among possible values of a sample statistic such as the sample mean. The appeal of the bootstrap is that we can use it to make an inference about some experimental result when the statistical theory is uncertain or even unknown. We can also use the bootstrap to assess how well the statistical theory holds: that is, whether an inference we make from a hypothesis test or confidence interval is justified.
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Statistical inferences were conducted using nonparametric bootstrapping estimation with 1000 repetitions.
“We conducted statistical inferences using nonparametric bootstrapping estimation (1000 repetitions), which does not make distributional assumptions on the data 57.”
From The Analgesic Effect of Oxytocin in Humans: A Double‐Blind, Placebo‐Controlled Cross‐Over Study Using Laser‐Evoked Potentials (2016) · cites this paper as [57]
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- Authors
- Curran-Everett, D.
- Affiliations
- Division of Biostatistics and Bioinformatics, National Jewish Health, and Department of Biostatistics and Informatics and Department of Physiology and Biophysics, School of Medicine, University of Colorado Denver, Denver, Colorado
- Venue
- Advances in Physiology Education
- Publisher
- American Physiological Society
- Published
- 2009-12
- Volume
- 33
- Issue
- 4
- Pages
- 286-292
- ISSN
- 1043-4046 (ISSN-L)
- 1522-1229
- OpenAlex
- W2144483020
- Cited by
- 52
- References
- 42
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 3 · 2022: 1 · 2021: 2 · 2020: 6 · 2019: 4 · 2018: 3 · 2017: 3 · 2016: 2 · 2015: 3 · 2014: 7 · 2013: 3 · 2012: 8
- FWCI
- 3.32
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- AJP Advances in Physiology Education (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- bootstrapping, statistical inference, sample mean, hypothesis testing, confidence intervals
- MeSH terms
- Humans, Software, Statistics as Topic, Models, Statistical
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