Sheppard Correction for Binned Variance

Problem

When data are grouped into bins of width h, the within-bin grouping inflates the variance by about h^2 / 12; the corrected variance subtracts that term.

Given the binned variance and the bin width, return the Sheppard-corrected variance (floored at zero).

Hint

Subtract h^2 / 12 and do not allow negative values.

Test cases

case 1

in: [2,1]

expected: 1.9166666666666667

case 2

in: [0.1,1]

expected: 0.016666666666666677

case 3

in: [0.084,0.5]

expected: 0.06316666666666668

Starter codePython

def sheppard_correction_for_binned_variance(binned_variance, bin_width):
    # Your code here
    pass

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