The manager of a fast food restaurant wants to determine how sales in a given week are related to the number of discount vouchers (#) printed in the local newspaper during the week. The number of vouchers and sales ($000s) from 10 randomly selected weeks is given below with Excel regression output.

\begin{array} { | c | c | } \hline \text { Number of vouchers } & \text { Sales } \\\hline 4 & 12.8 \\\hline 7 & 15.4 \\\hline 5 & 13.9 \\\hline 3 & 11.2 \\\hline 19 & 18.7 \\\hline 10 & 17.9 \\\hline 8 & 16.8 \\\hline 6 & 15.9 \\\hline 3 & 11.5 \\\hline 5 & 13.9 \\\hline\end{array}

\begin{array}{|l|c|c|c|c|c|l|}\hline \text { SUMMARY OUTPUT } & \\\hline & \\\hline \text { Regression Statistics } & \\\hline \text { Multiple R } & 0.8524 \\\hline \text { R Square } & 0.7267 \\\hline \text { Adjusted R Square } & 0.6925 \\\hline \text { Standard Error } & 1.4301 \\\hline \text { Observations } & 10 \\\hline & \\\hline \text { ANOvA } & & & & & & \\\hline & d f & S S & M S & F & \text { Significance } F & \\\hline \text { Regression } & 1 & 43.4982 & 43.4982 & 21.2682 & 0.0017 & \\\hline \text { Residual } & 8 & 16.3618 & 2.0452 & & & \\\hline \text { Total } & 9 & 59.8600 & & & & \\\hline\\\hline & \text { Coeficients } & \begin{array}{c}\text { Standard } \\\text { Error }\end{array} & t \text { Stat } & \text { P-value } & \text { Lower } 95 \% & \begin{array}{c}\text { Upper } \\95 \%\end{array} \\\hline \text { Intercept } & 11.5676 & 0.8341 & 13.8679 & 0.0000 & 9.6441 & 13.4912 \\\hline \text { Number of vouchers } & 0.4618 & 0.1001 & 4.6117 & 0.0017 & 0.2309 & 0.6927 \\\hline\end{array}

Interpret the coefficient of correlation.

In Regression Analysis, If the Coefficient of Correlation Is -1

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