Sampling distributions and the bootstrap

Sampling distributions and the bootstrap

  • 09/02/2022
    1:00 pm - 2:30 pm

Course details

statistics seminar | level: intermediate | register now
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affiliation: Ghent University


This seminar is about Resampling Techniques:

Resampling techniques are statistical procedures that re-use the sample data for the purpose of statistical
inference. For example: they can be used to estimate the variance and/or the bias of an estimator, construct
different types of confidence or prediction intervals and perform hypothesis tests about a parameter being
estimated. They are mostly relevant when parametric assumptions cannot be verified in practice due to small
samples, when joint distributions become too complex that closed forms cannot be obtained or for model
validation. We are going to consider four resampling techniques: permutations, cross-validation, bootstrap and the
jackknife with examples in R.


Background readings

Efron, Bradley. The Jackknife, the Bootstrap and Other Resampling Plans. Philadelphia (Pa.): Society for industrial and applied mathematics, 1982.






Emmanuel Abatih

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