FUNDAMENTALS OF COMPUTER

Detailed explanation-1: -Bootstrapping is any test or metric that uses random sampling with replacement (e.g. mimicking the sampling process), and falls under the broader class of resampling methods. Bootstrapping assigns measures of accuracy (bias, variance, confidence intervals, prediction error, etc.) to sample estimates.

Detailed explanation-2: -The bootstrap method is a resampling technique used to estimate statistics on a population by sampling a dataset with replacement. It can be used to estimate summary statistics such as the mean or standard deviation.

Detailed explanation-3: -Technically speaking, the bootstrap sampling method is a resampling method that uses random sampling with replacement.

Detailed explanation-4: -Resampling with replacement involves taking the original sample and using a random number generator to pick a number from the dataset. This number is then kept in the dataset so that it can be chosen again, and a new number is randomly selected. This process is repeated until a new sample of size n is created.

Detailed explanation-5: -Bootstrap samples. Which of the following statements is true about a Bootstrap Distribution? Bootstrap samples are generated by sampling with replacement from the original population.