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DataMListic
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Bootstrap resampling estimates uncertainty from a single sample — by treating that sample as if it were the entire population, then drawing new samples from it with replacement. Each resample gives a new mean, and stacking hundreds of them into a histogram gives you the bootstrap distribution. Chop off the bottom and top 2.5%, and you have a ...
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