Answer
$ŷ=146-1.187x_1+1.7x_2+3.65x_3+0.139x_4$
There is enough evidence to conclude that there exists a linear relation between at least one of the explanatory variables and the response variable.
No slope coefficient is significantly different from zero.
Work Step by Step
In MINITAB, enter the $x_1$ values in C1, 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 C1 C2 C3 C4 in "Continuous Predictors"
The least-squares regression line will be shown in "Regression Equation", where C5 is $ŷ$, C1 is $x_1$, C2 is $x_2$, C3 is $x_3$ and C4 is $x_4$
$ŷ=146-1.187x_1+1.7x_2+3.65x_3+0.139x_4$
$H_0: β_1=β_2=β_3=β_4=0$ versus $H_1: at~least~one~β_i\ne0$
$F_0=5.00$ with a P-value $=0.032\ltα$. Reject the null hypothesis.
1) $H_0: β_1=0$ versus $H_1: β_1\ne0$
$t_0=-1.37$ with a P-value $=0.213\ltα$. Do not reject the null hypothesis.
2) $H_0: β_2=0$ versus $H_1: β_2\ne0$
$t_0=0.10$ with a P-value $=0.925\ltα$. Do not reject the null hypothesis.
3) $H_0: β_3=0$ versus $H_1: β_3\ne0$
$t_0=1.15$ with a P-value $=0.289\ltα$. Do not reject the null hypothesis.
4) $H_0: β_4=0$ versus $H_1: β_4\ne0$
$t_0=0.21$ with a P-value $=0.837\ltα$. Do not reject the null hypothesis.
