# R squared for two variables

Assume we have two variables $X_1$ and $X_2$. If I do a linear regression of $Y$ on $X_1$, I have $R_1^2$. Similarly, I get $R_2^2$ for regression of $Y$ on $X_2$. If I run a regression of $Y$ on $X_1$ and $X_2$ together and assume that $R_1^2+R_2^2 < 1$, would it be possible to get a total $R^2$ larger than $R_1^2+R_2^2$ ?

My gut feeling is impossible, $R_1^2+R_2^2$ must be the upper bound since this is the maximum acquired when $X_1$ and $X_2$ are independent.

I have seen posts here and here. However, I'm still not sure whether we can get a range for the $\rho_{12}$, which is the correlation between those 2 variables, from $R_1^2$ and $R_2^2$, so that at least we can use that to analyze the range for the total $R^2$ below: $$R^2 = \frac{R_1^2 + R_2^2 - 2R_1R_2\rho_{12}}{1-\rho^2_{12}}$$.

Also, it would be fantastic if someone could point out a more intuitive or geometry explanation. Thanks.

Yes, it is possible. If both $X_1$ and $X_2$ are positively correlated with $Y$ but negatively correlated with each other.