Given the model $Y = \beta_0 + \beta_1 X + \epsilon$ with $n$ observations, consider the leverage $h_{ii}$ of the $i$-th observation. Which statement about the diagonal elements of the hat matrix $\mathbf{H} = \mathbf{X}(\mathbf{X}^T\mathbf{X})^{-1}\mathbf{X}^T$ is mathematically correct?