MSm SSᵣ/p
F₀ = --- = -----------
MSₑ SSₑ/(n - p - α)
where:
MSm = mean square model (regression mean square) = SSᵣ / df(SSᵣ) = SSᵣ/p
MSₑ = mean square error (estimate of variance σ² of the random error)
= SSₑ/(n - p - α)
p = the order of the fitted polynomial
α = 1 if the model includes a constant term, 0 otherwise. (p+α = total number of model parameters)
SSᵣ = sum of squares of the regression
SSₑ = sum of squares of residuals
