Imagine a scenario where you want to assess the stability of a statistical estimator. How would Bootstrapping help in this context?
- By fixing the bias in the estimator
- By increasing the size of the dataset
- By repeating the sampling process with replacement and calculating the variance
- By repeating the sampling process without replacement
Bootstrapping assesses the stability of a statistical estimator by repeating the sampling process with replacement and calculating variance, standard error, or other statistics. By creating numerous "bootstrap samples," it allows insights into the estimator's distribution, thereby providing a measure of its stability and reliability.
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