Bootstrapping is especially useful when …
A) the sample size that we are working with is small.
B) the sample size that we are working with is large.
C) the sampling distribution of is approximately normal.
D) the distribution is symmetric.

Question

Bootstrapping is especially useful when …
A) the sample size that we are working with is small. 
B) the sample size that we are working with is large. 
C) the sampling distribution of is approximately normal. 
D) the distribution is symmetric.

Quizplus · Accepted Answer

Bootstrapping is a resampling technique that simulates repeated sampling from a given dataset to obtain an estimate of a population parameter or to construct a confidence interval for it. It is useful when the sample size is small because it allows us to make inferences about the population parameter without relying on the assumptions of a specific statistical test or the population distribution. Bootstrapping can also be used with larger sample sizes but may become computationally intensive.

Bootstrapping Is Especially Useful When …