Resampling Methods in Statistics

To reduce the computational requirements of fitting statistical models

To decrease the variability of a linear regression fit

To fit a model of interest once on the training set

To draw samples from a training set and refit a model to obtain additional information (correct)

Because they use the original training sample multiple times

Because they involve fitting the same statistical method multiple times using different subsets of the training data (correct)

Due to recent advances in computing power

Because they involve fitting the statistical method only once

Information about the mean of the data points

Information about outliers in the data

Information about the intercept of a linear regression model

Information about the variability of the fitted model (correct)

<p>Because they allow for estimating test error and evaluating model performance</p> Signup and view all the answers

<p>Advances in computing power</p> Signup and view all the answers

<p>To evaluate the performance of a statistical learning method</p> Signup and view all the answers