Answer
After removing $x_1$:
$ŷ =282.3+1.143x_2+0.394x_3-2.957x_4$
$F_0=62.29$ with a P-value $\lt0.001\ltα$. The model is significant.
After removing $x_3$:
$ŷ =281.6+1.158x_2-2.627x_4$
$F_0=76.89$ with a P-value $\lt0.001\ltα$. The model is significant.
Work Step by Step
Let's remove $x_1$, the explanatory variable with the highest P-value (see item (b)).
In MINITAB, enter the $x_2$ values in C2, the $x_3$ values in C3, the $x_4$ values in C4 and the $y$ values in C5.
Select Stats -> Regression -> Regression -> Fit Regression Model
Enter C5 in "Responses" and C2 C3 C4 in "Continuous Predictors"
The least-squares regression line will be shown in "Regression Equation", where C5 is $ŷ$ , C2 is $x_2$, C3 is $x_3$ and C4 is $x_4$
Click OK.
$ŷ =282.3+1.143x_2+0.394x_3-2.957x_4$
$F_0=62.29$ with a P-value $\lt0.001\ltα$
Now, let's remove $x_3$ because its P-value is greater than $α$:
In MINITAB, enter the $x_2$ values in C2, the $x_4$ values in C4 and the $y$ values in C5.
Select Stats -> Regression -> Regression -> Fit Regression Model
Enter C5 in "Responses" and C2 C4 in "Continuous Predictors"
The least-squares regression line will be shown in "Regression Equation", where C5 is $ŷ$ , C2 is $x_2$ and C4 is $x_4$
Click OK.
$ŷ =281.6+1.158x_2-2.627x_4$
$F_0=76.89$ with a P-value $\lt0.001\ltα$
