What is bootstrapping in statistics?
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What is bootstrapping in statistics?
Bootstrapping is a resampling technique used to estimate the distribution of a statistic by repeatedly sampling with replacement from the data.
How does bootstrapping differ from traditional statistical methods?
Unlike traditional methods that rely on assumptions about the data distribution, bootstrapping makes fewer assumptions and can be applied to a wider range of problems.
Can you give me an example of how to use bootstrapping?
Sure! If you have a sample of data, you can create many new samples by randomly selecting data points with replacement, then calculate the statistic of interest for each sample.
What are the advantages of using bootstrapping?
Bootstrapping allows for better estimation of confidence intervals and can be used with small sample sizes or non-normal data.
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