8. Hayes Consulting Company builds database and point-of-sale systems for golf courses and country clubs. Mr. Hayes is trying to determine total revenues for the coming year and feels he can estimate revenues based on the number of customers each month. He gathers the following data for the prior 12 months: He performed a regression analysis on the data provided (output below). Is there a strong correlation between Hayes Consulting's revenues and the number of customers? \begin{tabular}{lr} \hline \multicolumn{2}{c}{ Regression Stotiatics } \\ \hline Multiple R & 0.991749555 \\ A Square & 098356718 \\ Adjusted A Square & 0.981923898 \\ Standard Error & 61692.41626 \\ Observations & 12 \\ \hline \end{tabular} ANOVA \begin{tabular}{|c|c|c|c|c|c|} \hline & df & 55 & MS & f & Significancef \\ \hline Negresion & 1 & 2278016+12 & 2.278016+12 & 5985382733 & 2.96931610 \\ \hline Residual & 10 & 30059542234 & 3805954223 & & \\ \hline Total & 11 & 2.31607[+12 & & & \\ \hline \end{tabular} \begin{tabular}{|c|c|c|c|c|c|c|c|c|} \hline & Corfficients & Standard Emer & istet & Pvolue & Lower 9SS & Upper 955 & tower 95.0W & Upper 95 on \\ \hline intercept & & 9229956502 & 0.952611798 & 0.358441447 & 116507,9763 & 29505.8543 & -1168079763 & 294505.9543 \\ \hlinex variable 1 & 11917.63906 & 487.1203138 & 24.46504186 & 2.96931610 & 10432.2473 & 13003.03081 & 10432.2473 & 13003.03011 \\ \hline \end{tabular}