bootstrap resampling
[ˈbuːtstræp ˌriːˈsæmplɪŋ]
nounpl: bootstrap resamplings
reamostragem bootstrap
1. A statistical resampling technique where samples are repeatedly drawn with replacement from an original dataset to estimate the distribution of a statistic or to assess the reliability of an estimator
Bootstrap resampling allows us to estimate confidence intervals without assuming a specific probability distribution.
A reamostragem bootstrap nos permite estimar intervalos de confiança sem assumir uma distribuição de probabilidade específica.
2. A computational method in statistics that uses random sampling with replacement to create multiple simulated datasets from a single observed sample
The researcher used bootstrap resampling to validate the stability of the regression model.
O pesquisador utilizou reamostragem bootstrap para validar a estabilidade do modelo de regressão.
Bootstrap resampling is a cornerstone technique in modern computational statistics and machine learning, widely used in both Brazilian and American academic institutions. The term 'bootstrap' in English carries the metaphorical sense of self-improvement without external help, which aligns with the statistical method's ability to estimate distributions from data alone. In Portuguese-speaking countries, the term is often kept in English within technical and academic circles but may be translated for educational or public communication purposes.
Related Idioms & Phrases
pulling yourself up by your bootstraps (related to the metaphorical meaning of bootstrap)
bootstrap approach (generic term for self-sufficient methods)
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