Answer
$ŷ=24.1+0.0718x_1+54.9x_3$
All the slopes are significantly different from zero.
There is enough evidence to conclude that there is a linear relation between square footage and baths with asking price.
Work Step by Step
Let's remove the explanatory variable bedrooms (the highest P-value).
In MINITAB, enter the Square Footage values in C1, the Baths values in C3 and the Asking Price values in C4.
Select Stats -> Regression -> Regression -> Fit Regression Model
Enter C4 in "Responses" and C1 C3 in "Continuous Predictors"
The least-squares regression line will be shown in "Regression Equation", where C4 is $ŷ$ (Asking Price), C1 is $x_1$ (Square Footage) and C3 is $x_3$ (Baths).
$ŷ=24.1+0.0718x_1+54.9x_3$
1) $H_0: β_1=0$ versus $H_1: β_1\ne0$
$t_0=2.77$ with a P-value $=0.020\ltα=0.05$. Reject the null hypothesis.
2) $H_0: β_3=0$ versus $H_1: β_3\ne0$
$t_0=2.49$ with a P-value $=0.032\ltα=0.05$. Reject the null hypothesis.
