Consider the linear regression model y_i = \beta_0 + \beta_1 x_i + \in_i , i = 1,2,\dots, 6 where \beta_0 and \beta_1 are unknown parameters and \in_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)