Summary
Statistical inference to evaluate the uncertainty/variability of estimations is usually challenging in classical statistics. But this is not true when resampling methods are used, data-oriented methods to make valid inference, perfectly suited for data scientists.
The bootstrap is a general tool to estimate the variance of an estimator. The estimation of the variance of a very complex statistic is as easy as estimating the variance of a simple estimator such as the arithmetic mean.
We saw that another popular resampling method – the jackknife – is by far not as trustable as the bootstrap, especially for non-smooth estimators. However, the jackknife is a useful tool to estimate the variance of the bootstrap variance estimate, for example. ...
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