Least squares prediction from sums of squares and products

Based on $20$ observations $(x_1,y_1),…,(x_{20},y_{20})$, the following values are obtained: $\sum_{i=1}^{20}x_i=6$, $\sum_{i=1}^{20}x_i^2=14$, $\sum_{i=1}^{20}y_i=9$ and $\sum_{i=1}^{20}x_iy_i=20$. For $X=1$, the predicted value of $Y$ based on a least squares fit of a linear regression model of $Y$ on $X$ is ___________.