You Run a Regression Analysis and Receive the Following Results

You run a regression analysis and receive the following results:
SUMMARY OUTPUT
$\begin{array}{l}\begin{array} { l r } \hline{ \text { Regression Statistics } } \\\hline \text { Multiple R } & 0.88000000 \\\text { R Square } & 0.78219168 \\\text { Adjusted R Square } & 0.70958891 \\\text { Standard Error } & 1165.19000 \\\text { Observations } & 5 \\\hline\end{array}\\\\\begin{array} { l c r c c r } \hline & d f & S S & M S & F & \text { Significance } F \\\hline \text { Regression } & 1 & 14626984.4 & 1 \mathrm { E } + 07 & 10.7736 & 0.0463451 \\\text { Residual } & 3 & 4073015.604 & 1 \mathrm { E } + 06 & & \\\text { Total } & 4 & 18700000 & & & \\\hline\end{array}\\\\\begin{array} { l r r r c } \hline & \text { Coefficients } & \text { Standard Error } & t \text { Stat } & P \text {-value } \\\hline \text { Intercept } & 16146.37 & 8167.49 & 1.977 & 0.14249 \\\text { X Variable 1 } & 2.380 & 0.730 & 3.282 & 0.04635 \\\hline\end{array}\end{array}$
-To the nearest dollar,what would be the estimated total costs if 500 units were produced?

A) $ 544
B) $4236
C) $3692
D) $3147