Numpy Beginner's Guide (Update)

Bootstrapping in statistics

Bootstrapping is a method used to estimate variance, accuracy, and other metrics of sample estimates, such as the arithmetic mean. The simplest bootstrapping procedure consists of the following steps:

1. Generate a large number of samples from the original data sample having the same size N. You can think of the original data as a jar containing numbers. We create the new samples by N times randomly picking a number from the jar. Each time we return the number into the jar, so a number can occur multiple times in a generated sample.
2. With the new samples, we calculate the statistical estimate under investigation for each sample (for example, the arithmetic mean). This gives us a sample of possible values for the estimator. ...