Goodness of fit
R-squared
The coefficient of determination (R-squared or R2) provides a measure of the goodness of fit
for the estimated regression equation.
R2 = SSR/SST = 1 – SSE/SST
Values of R2 close to 1 indicate perfect fit, values close to zero indicate poor fit.
R2 that is greater than 0.25 is considered good in the economics field.
R-squared interpretation: if R-squared=0.8 then 80% of the variation is explained by the
regression and the rest is due to error. So, we have a good fit.
Adjusted R-squared
Problem: R2 always increases when a new independent variable is added. This is because the
SST is still the same but the SSE declines and SSR increases.
Adjusted R-squared corrects for the number of independent variables and is preferred to R-
squared.
ܴଶ ൌ 1 െ ሺ1 െ ܴଶሻ ݊െ1 ݊െെ1
where p is the number of independent variables, and n is the number of observations.