Instruction 12 $\text { Regression statistics }$ $\text { ANOVA }$

Instruction 12.33
It is believed that the average numbers of hours spent studying per day (HOURS) during undergraduate education should have a positive linear relationship with the starting salary (SALARY, measured in thousands of dollars per month) after graduation. Given below is the Microsoft Excel output for predicting starting salary (Y) using number of hours spent studying per day (X) for a sample of 51 students. NOTE: Only partial output is shown.
$\text { Regression statistics }$
$\begin{array}{|l|l|}\hline \text { Multiple R } & 0.8857 \\\hline \text { R Square } & 0.7845 \\\hline \begin{array}{l}\text { Adjusted R } \\\text { Square }\end{array} & 0.7801 \\\hline \text { Standard Error } & 1.3704 \\\hline \text { Observations } & 51\\\hline\end{array}$

$\text { ANOVA }$
$\begin{array}{|l|l|l|l|l|l|}\hline & d f & S S & M S & F & \begin{array}{l}\text { Significance } \\F\end{array} \\\hline \text { Regression } & 1 & 335.0472 & 335.0473 & 178.3859 & \\\hline \text { Residual } & & & 1.8782 & & \\\hline \text { Total } & 50 & 427.0798 & & & \\\hline\end{array}$

$\begin{array}{|l|l|l|l|l|l|l|} \hline& \text { Coefficients } & \begin{array}{l}\text { Standard } \\\text { Error }\end{array} & \text { t Stat } & \text { p-value } & \text { Lower 95\% } & \text { Upper 95\% } \\\hline \text { Intercept } & -1.8940 & 0.4018 & -4.7134 & 2.051 \mathrm{E}-05 & -2.7015 & -1.0865 \\\hline \text { Hours } & 0.9795 & 0.0733 & 13.3561 & 5.944 \mathrm{E}-18 & 0.8321 & 1.1269\\\hline\end{array}$ Note: 2.051E-05 = 2.051 * 10^-0.5 and 5.944E-18 = 5.944 * 10^-18.
-Referring to Instruction 12.33,the 90% confidence interval for the average change in SALARY (in thousands of dollars) as a result of spending an extra hour per day studying is

A) narrower than [-2.70159, -1.08654].
B) narrower than [0.8321927, 1.12697].
C) wider than [-2.70159, -1.08654].
D) wider than [0.8321927, 1.12697].