Sum of least squares regression estimates

Consider the linear regression model $y_i=\beta_0+\beta_1 x_i+\epsilon_i, i=1, 2, \dots, 6$, where $\beta_0$ and $\beta_1$ are unknown parameters and $\epsilon_i$'s are independent and identically distributed random variables having $N(0, 1)$ distribution. The data on $(x_i, y_i)$ are given in the following table.

| $x_i$ | 1.0 | 2.0 | 2.5 | 3.0 | 3.5 | 4.5 | |—|—|—|—|—|—|—| | $y_i$ | 2.0 | 3.0 | 3.5 | 4.2 | 5.0 | 5.4 |

If $\hat{\beta}_0$ and $\hat{\beta}_1$ are the least squares estimates of $\beta_0$ and $\beta_1$, respectively, based on the above data, then $\hat{\beta}_0+\hat{\beta}_1$ equals __________ (round off to $2$ decimal places)