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

question 185

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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, the error sum of squares (SSE) of the above regression is

Identify the components that establish standard time for a task.
Distinguish between different time study techniques and their uses.
Recognize the significance of allowances and performance ratings in setting labor standards.
Understand the calculation of normal time and standard time from observed data.

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