A small independent organic food store offers a variety of specialty coffees.To determine Whether price has an impact on sales, the managers kept track of how many pounds of each Variety of coffee were sold last month.

\begin{array} { | l | l | l | } \hline & \text { PRICE PER POUND } & \text { POUNDS SOLD } \\\hline & \$ 3.99 & 75 \\\hline & \$ 5.99 & 60 \\\hline & \$ 7.00 & 65 \\\hline & \$ 12.00 & 45 \\\hline & \$ 4.50 & 80 \\\hline & \$ 7.50 & 70 \\\hline & \$ 15.00 & 25 \\\hline & \$ 10.00 & 35 \\\hline & \$ 12.50 & 40 \\\hline & \$ 8.99 & 50\\\hline & \\\hline \text { Mean } &\$8.75&54.50 \\\hline \begin{array} { l } \text { Standard } \\\text { Deviation }\end{array} & \$ 3.63 & 18.33 \\\hline \text { Correlation } & - \mathbf { 0 . 9 2 7 } \\\hline\end{array}

Based on the data and summary statistics, the intercept of the estimated regression line that Relates the response variable (monthly sales) to the predictor variable (price per pound) is
A)95.459.
B).858.
C)-4.684.
D)-.858.
E)-8.999.

An Article in the Journal of Statistics Education Reported the Price

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