According to the least-squares principle, the regression line is the one that makes the sum of squared residuals as small as possible. Refer to the dinner duration data in the table below and use the regression equation.
$\hat{y}=1.10+0.102x$
Identify the 10 residuals by comparing the actual tip to the predicted tip for each observation.

$0.20;0.09;0.03;0.07;-0.6;0.09;0.01;0.03;-0.03;0.09$

$-0.46;0.09;0.03;0.07;0.06;0.00;-0.01;0.03;-0.03;0.09$

$-0.20;0.09;0.03;0.07;0.06;0.00;-0.01;0.03;-0.03;-0.09$

$0.50;0.09;-0.03;0.07;-0.06;0.00;0.01;0.01;-0.03;-0.04$