After some experimentation, you have observed the following data concerning the relationship between marketing and sales. Use Excel's curve fitting method to find the best quadratic equation to model this relationship.
$\begin{array}{|l|l|l|l|l|l|}
\hline \begin{array}{l}
\text { Marketing } \
(\$)
\end{array} & 100 & 110 & 120 & 130 & 140 \
\hline \begin{array}{l}
\text { Sales } \
(\$ 100)
\end{array} & 310 & 500 & 600 & 690 & 780 \
\hline
\end{array}
\begin{array}{r|r|r|r|r|r|}
\hline \150 & 160 & 170 & 180 & 190 & 200 \
\hline \850 & 925 & 1,000 & 1,050 & 1,09 & 1,120 \
\hline
\end{array}$
A) ?0.055x2 + 24x ? 1516
B) 0.055x2 + 24x ? 1516
C) ?0.055x2 ? 24x ? 1516
D) ?0.055x2 + 24x + 1516
E) ?0.11x2 + 24x ? 1516

Question

Quizplus · Accepted Answer

The correct quadratic equation to model the relationship between marketing and sales, based on Excel's curve fitting method, is likely to be $−0.055x^2 + 24x − 1516$. This is because a quadratic equation in the form of $ax^2 + bx + c$ can model the parabolic trend that might be observed in the given data, and the negative coefficient for $x^2$ suggests the graph opens downwards, which could fit the increasing then decreasing trend of sales with increased marketing spend.

After Some Experimentation, You Have Observed the Following Data Concerning