Bootstrap Standard Error

Problem

Compute the bootstrap standard error of the mean. Call random.seed(seed) and draw num_samples resamples of size n with replacement (random.randrange), then return the population standard deviation of the resample means.

Empty data or non-positive num_samples returns 0.0.

Hint

Standard error is the standard deviation of the bootstrap distribution of the mean.

Test cases

case 1

in: [[1,2,3,4,5,6,7,8],200,42]

expected: 0.8154140052758475

case 2

in: [[10,12,11,13,12],100,7]

expected: 0.4281074631444773

case 3

in: [[5],50,1]

expected: 0

case 4

in: [[],10,0]

expected: 0

Starter codePython

import random
def bootstrap_standard_error(data, num_samples, seed):
    # Your code here
    pass

4 test cases · run your code against them in the editor