Residual Standard Error

Problem

Fit simple linear regression y = a + b*x by least squares and return the residual standard error sqrt(SSE/(n-2)). Return 0.0 when n < 3, the lengths differ, or x has zero variance.

Hint

Compute the slope from Sxy/Sxx, then the sum of squared residuals.

Test cases

case 1

in: [[1,2,3],[2,4,6]]

expected: 0

case 2

in: [[1,2,3,4],[2,3,4,7]]

expected: 0.7745966692414836

case 3

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

expected: 0.408248290463863

case 4

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

expected: 0

case 5

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

expected: 0

Starter codePython

def residual_standard_error(x, y):
    # Your code here
    pass

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