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

question 169

Multiple Choice

Instruction 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 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.
$\begin{array}{|l|r|}\hline {\text { Regression Statistics }} \\\hline \text { Multiple R } & 0.8857 \\\hline \text { R Square } & 0.7845 \\\hline \text { Adjusted R Square } & 0.7801 \\\hline \text { Standard Error } & 1.3704 \\\hline \text { Observations } & 51 \\\hline\end{array}$
ANOVA
$\begin{array}{|l|r|r|r|r|r} & d f & \text { SS } & {M S} & F & \text { Significance } F \\\hline \text { Regression } & 1 & 335.0472 & 335.0473 & 178.3859 & \\\hline \text { Residual } & & & 1.8782 & & \\\hline \text { Total } & 50 & 427.0798 & & &\end{array}$

$\begin{array}{l|r|r|r|r|r|r} & \text { Coefficients } & \begin{array}{c}\text { Standard } \\\text { Error }\end{array} & \text { t Stat } & \text { P-value } & \text { Lower 95\% } & \text { Upper 95\% } \\\hline \text { Intercept } & -1.8940 & 0.4018 & -4.7134 & 2.051 \mathrm{E}-05 & -2.7015 & -1.0865 \\\hline \text { Hours } & 0.9795 & 0.0733 & 13.3561 & 5.944 \mathrm{E}-18 & 0.8321 & 1.1269\end{array}$ Note: 2.051E-05 = 2.051 * 10^-0.5 and 5.944E-18 = 5.944 * 10^-18.
-Referring to Instruction 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

• A)5.944E - 18.
• B)(2.051E - 05)/ 2.
• C)2.051E - 05.
• D)(5.944E - 18)/ 2.

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Definitions:

Variance

A measure of the dispersion of a set of data points, calculated as the average squared deviation from the mean of the data.

Standard Deviation

A measure of the amount of variation or dispersion of a set of values, indicating how spread out the data points are.

Range

The difference between the highest and lowest values in a dataset, indicating the spread of the data.

Variability

A statistical measure that describes the dispersion or spread of data points in a data set.