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

question 197

Multiple Choice

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.
 Regression statistics \text { Regression statistics }
 Multiple R 0.8857 R Square 0.7845 Adjusted R  Square 0.7801 Standard Error 1.3704 Observations 51\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}

 ANOVA \text { ANOVA }
dfSSMSF Significance F Regression 1335.0472335.0473178.3859 Residual 1.8782 Total 50427.0798\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}

 Coefficients  Standard  Error  t Stat  p-value  Lower 95%  Upper 95%  Intercept 1.89400.40184.71342.051E052.70151.0865 Hours 0.97950.073313.35615.944E180.83211.1269\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,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:

Collateral

Assets pledged by a borrower to secure a loan or credit, which can be seized by the lender if the loan is not repaid.

Auto Sales & Finance

The business operations related to selling automobiles to consumers, usually involving financing options to assist with the purchase.

Co-Surety

A joint surety; one who assumes liability jointly with another surety for the payment of an obligation.

Debtor

An individual or organization that owes money or debt to another entity.

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