Bootstrapping is useful because it adds more values to the original data set.
A)True.You are able to add as many new values as needed to the original data set.
B)True.You are able to add a finite amount of new values to the original data set.
C)False.No new values are added to the data set.
D)False.Bootstrapping is only used to change the mean of the original data set.

Question

Quizplus · Accepted Answer

Bootstrapping is a statistical method that resamples the original dataset with replacement to create many simulated samples. It does not add new values to the dataset; instead, it helps in estimating the distribution of a statistic (e.g., mean, variance) by sampling from the existing data.

Bootstrapping Is Useful Because It Adds More Values to the Original