The Following MINITAB Output Presents a Multiple Regression Equation $\hat { y } = b _ { 0 } + b _ { 1 } x _ { 1 } +$

The following MINITAB output presents a multiple regression equation $\hat { y } = b _ { 0 } + b _ { 1 } x _ { 1 } +$ $b _ { 2 } x _ { 2 } + b _ { 3 } x _ { 3 } + b _ { 4 } x _ { 4 }$
The regression equation is
$$\mathrm{Y}=3.9695+1.4577 \mathrm{X} 1-1.7859 \mathrm{X} 2+0.7686 \mathrm{X} 3+0.0777 \mathrm{X} 4$$

$\begin{array}{lllll}\text { Predictor } & \text { Coef } & \text { SE Coef } & \text { T } & \text { P } \\\text { Constant } & 3.9695 & 0.8785 & 0.9299 & 0.327 \\\text { X1 } & 1.4577 & 0.6034 & 3.5107 & 0.003 \\\text { X2 } & -1.7859 & 0.7302 & -3.1148 & 0.005 \\\text { X3 } & 0.7686 & 0.6732 & 1.9294 & 0.088 \\\text { X4 } & 0.0777 & 0.7569 & -1.0782 & 0.352\end{array}$

$\mathrm{S}=2.2610 \quad \mathrm{R}-\mathrm{Sq}=51.5 \% \mathrm{R}-\mathrm{Sq}(\mathrm{adj}) =44.8 \%$

$\begin{array}{l}\text { Analysis of Variance }\\\begin{array}{lcccrr}\text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F P } & \\\text { Regression } & 4 & 1148.7 & 287.2 & 9.0031 & 0.003 \\\text { Residual Error } & 34 & 1083.9 & 31.9 & & \\\text { Total } & 38 & 2232.6 & & & \\\hline\end{array}\end{array}$


Is the model useful for prediction? Use the $\alpha = 0.05$ level.

A) Yes
B) No