Jackknife Bias

Problem

Return the jackknife bias estimate (n-1) * (mean of leave-one-out population variances - full-sample population variance). Return 0.0 when n < 2.

Hint

Leave-one-out estimates reveal the finite-sample bias of the variance.

case 1

in: [[1,2,3,4,5]]

expected: -0.5

case 2

in: [[1,1,1]]

expected: 0

case 3

in: [[1,2]]

expected: -0.25

case 4

in: [[10,20,30]]

expected: -33.33333333333334

case 5

in: [[]]

expected: 0

Starter codePython

def jackknife_bias(data):
    # Your code here
    pass

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