You Run a Regression Analysis and Receive the Following Results

You run a regression analysis and receive the following results:
SUMMARY OUTPUT
$\begin{array}{l}\begin{array} { l r } \hline{ \text { Regression Statistics } } \\\hline \text { Multiple R } & 0.88000000 \\\text { R Square } & 0.78219168 \\\text { Adjusted R Square } & 0.70958891 \\\text { Standard Error } & 1165.19000 \\\text { Observations } & 5 \\\hline\end{array}\\\\\begin{array} { l c r c c r } \hline & d f & S S & M S & F & \text { Significance } F \\\hline \text { Regression } & 1 & 14626984.4 & 1 \mathrm { E } + 07 & 10.7736 & 0.0463451 \\\text { Residual } & 3 & 4073015.604 & 1 \mathrm { E } + 06 & & \\\text { Total } & 4 & 18700000 & & & \\\hline\end{array}\\\\\begin{array} { l r r r c } \hline & \text { Coefficients } & \text { Standard Error } & t \text { Stat } & P \text {-value } \\\hline \text { Intercept } & 16146.37 & 8167.49 & 1.977 & 0.14249 \\\text { X Variable 1 } & 2.380 & 0.730 & 3.282 & 0.04635 \\\hline\end{array}\end{array}$
-When using regression analysis to predict mixed cost behaviour,which of the following would be the independent variable?

A) The highest level of activity
B) The lowest level of activity
C) The mixed cost at a given level of production
D) The volume of production that drives a particular amount of mixed cost