The equation of the least squares regression line is y (hat)=1.3+0.73x. what is

We know that
The residual value is the observed value minus the predicted value.
RESIDUAL VALUE=[OBSERVED VALUE-PREDICTED VALUE]
where
Predicted value.--> the predicted value given the current regression equation
Observed value. --> The observed value for the dependent variable.

in this problem
predicted value  for x=4    y (hat)=1.3+0.73*4> 4.22
predicted value is 4.22

observed value is 7
so
RESIDUAL VALUE=[7-4.22]> 2.78

the answer is
the residual value is 2.78

The distributive property is like
-a(b + c - d) = (-a)(b) + (-a)(c) + (-)

so in this case (remember the negatives)
-2(2.1x + 3y - 1.8)
becomes
(-2)(2.1x) + (-2)(3y) + (-.8)

and simplifies to
-4.2x - 6y + 3.8