Briefly state two difference between a "bootstrap distribution" and a "randomization distribution".

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Bootstrapping is mainly focused on estimating population parameters, and it attempts to draw inferences about the population .Bootstrapping is a method that estimates the sampling distribution by taking multiple samples with replacement from a single random sample. We can also called them resamples. Each resample is the same size as the original sample. The original sample represents the population from which it was drawn.

While randomization procedures focus on the underlying mechanism that led to the data being distributed between groups.We can use a randomization distribution to determine how likely our sample statistic is given that the null hypothesis is true.The p-value is the proportion of samples on the randomization distribution that are more extreme than our observed sample in the direction of the alternative hypothesis.

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orchestra answered 1 year ago

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