import numpy as np x = [4, 8, 6, 5, 3] n = len(x) sum_x = sum(x) sum_x_sq = sum(xi**2 for xi in x) Sxx = sum_x_sq - (sum_x**2)/n variance = Sxx / (n-1) print(f"Sxx = Sxx, Variance = variance")

This version is the most intuitive because it shows exactly what variance is : the average of the squared deviations.

The of these values is: [ \barx = \frac1n \sum_i=1^n x_i ]

Here, ( S_xx ) is part of the denominator that standardizes the explained variation.

Sxx Variance Formula Page

import numpy as np x = [4, 8, 6, 5, 3] n = len(x) sum_x = sum(x) sum_x_sq = sum(xi**2 for xi in x) Sxx = sum_x_sq - (sum_x**2)/n variance = Sxx / (n-1) print(f"Sxx = Sxx, Variance = variance")

This version is the most intuitive because it shows exactly what variance is : the average of the squared deviations. Sxx Variance Formula

The of these values is: [ \barx = \frac1n \sum_i=1^n x_i ] import numpy as np x = [4, 8,

Here, ( S_xx ) is part of the denominator that standardizes the explained variation. Sxx Variance Formula