# R-Squared for a non linear curve

At the start, please forgive me if my question is too elementary.

I am fitting a non-linear curve. Say a parabola. The data points I have are close to a parabola and the best output I get is a parabola. I want to quantify the quality if fit. Something like an R-Squared metric. I was wondering if the R-Squared metric, like in the case of a linear OLS, makes sense since one of the inputs for R-squared is the average of the input values, which I'm not sure makes sense for a parabola.

OLS quadratic model: $$y = \beta_0 + \beta_1 X + \beta_2 X^2$$
Your model is still a linear function of the unknown parameters $$\beta$$ with the features $$X$$ and $$X^2$$. Hence $$R^2$$ is still applicable.