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SCENARIO 12-9
It Is Believed That, the Average Numbers of Hours

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SCENARIO 12-9
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 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.  Regression Statistics  Multiple R 0.8857 R Square 0.7845 Adjusted R Square 0.7801 Standard Error 1.3704 Observations 51\begin{array}{lr}{\text { Regression Statistics }} \\\hline \text { Multiple R } & 0.8857 \\\text { R Square } & 0.7845 \\\text { Adjusted R Square } & 0.7801 \\\text { Standard Error } & 1.3704 \\\text { Observations } & 51 \\\hline\end{array}
ANOVA
dfSSMSF Significance F  Regression 1335.0472335.0473178.3859 Residual 1.8782 Total 50427.0798\begin{array}{lrrrrr} & d f & S S & M S & F & \text { Significance F } \\\hline \text { Regression } & 1 & 335.0472 & 335.0473 & 178.3859 \\\text { Residual } & & & 1.8782 & \\\text { Total } & 50 & 427.0798 & &\end{array}

 Coefficients  standered Error  tStat  P-value  Lower 95%  Upper 95%  Intercept 1.89400.40184.71340.00002.70151.0865 Hours 0.97950.073313.35610.00000.83211.1269\begin{array}{lrrrrrrr} & \text { Coefficients } & \text { standered Error } & \text { tStat } & \text { P-value } & \text { Lower 95\% } & \text { Upper 95\% } \\\hline \text { Intercept } & -1.8940 & 0.4018 & -4.7134 & 0.0000 & -2.7015 & -1.0865 \\\text { Hours } & 0.9795 & 0.0733 & 13.3561 & 0.0000 & 0.8321 & 1.1269\end{array} Note: 2.051E - 05 = 2.051 *10-05 and 5.944 E - 18 = 5.944 *10-18 .
-Referring to Scenario 12-9, to test the claim that SALARY depends positively on HOURS against the null hypothesis that SALARY does not depend linearly on HOURS, the p-value of the test statistic is _.


Definitions:

Investment Turnover

The ratio of sales to invested assets.

Profit Margin

A financial metric, calculated as net income divided by revenue, that indicates the percentage of sales that exceeds the costs of goods sold.

Return on Investment

A performance measure used to evaluate the efficiency or profitability of an investment, calculated by dividing net profit by the cost of the investment.

Sales to Investment

A ratio that measures the efficiency of a firm in generating sales from its investments in assets.

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