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SCENARIO 14-10
You Worked as an Intern at We Always

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SCENARIO 14-10
You worked as an intern at We Always Win Car Insurance Company last summer. You notice that
individual car insurance premiums depend very much on the age of the individual and the number of
traffic tickets received by the individual. You performed a regression analysis in EXCEL and
obtained the following partial information:  Regression  Statistics  Multiple R 0.8546 R Square 0.7303 Adjusted R Square 0.6853 Standard Error 226.7502 Observations 15\begin{array}{l}\hline{ \text { Regression } \text { Statistics } } \\\hline \text { Multiple R } & 0.8546 \\\text { R Square } & 0.7303 \\\text { Adjusted R Square } & 0.6853 \\\text { Standard Error } & 226.7502 \\\text { Observations } & 15 \\\hline\end{array}

 ANOVA \text { ANOVA }
 SCENARIO 14-10 You worked as an intern at We Always Win Car Insurance Company last summer. You notice that individual car insurance premiums depend very much on the age of the individual and the number of traffic tickets received by the individual. You performed a regression analysis in EXCEL and obtained the following partial information:  \begin{array}{l} \hline{ \text { Regression } \text { Statistics } } \\ \hline \text { Multiple R } & 0.8546 \\ \text { R Square } & 0.7303 \\ \text { Adjusted R Square } & 0.6853 \\ \text { Standard Error } & 226.7502 \\ \text { Observations } & 15 \\ \hline \end{array}    \text { ANOVA }      \begin{array} { l r r r r r r }  \hline & \text { Coefficients } & \text { Standard Error } & { \text { tStat } } & \text { P-value } & \text { Lower 99\% } & \text { Upper 99\% } \\ \hline \text { Intercept } & 821.2617 & 161.9391 & 5.0714 & 0.0003 & 326.6124 & 1315.9111 \\ \text { Age } & - 1.4061 & 2.5988 & - 0.5411 & 0.5984 & - 9.3444 & 6.5321 \\ \text { Tickets } & 243.4401 & 43.2470 & 5.6291 & 0.0001 & 111.3406 & 375.5396 \\ \hline \end{array}  -Referring to Scenario 14-10, the 99% confidence interval for the change in mean insurance premiums of a person who has become 1 year older (i.e., the slope coefficient for AGE) is -1.4061 ± _______.

 Coefficients  Standard Error  tStat  P-value  Lower 99%  Upper 99%  Intercept 821.2617161.93915.07140.0003326.61241315.9111 Age 1.40612.59880.54110.59849.34446.5321 Tickets 243.440143.24705.62910.0001111.3406375.5396\begin{array} { l r r r r r r } \hline & \text { Coefficients } & \text { Standard Error } & { \text { tStat } } & \text { P-value } & \text { Lower 99\% } & \text { Upper 99\% } \\\hline \text { Intercept } & 821.2617 & 161.9391 & 5.0714 & 0.0003 & 326.6124 & 1315.9111 \\\text { Age } & - 1.4061 & 2.5988 & - 0.5411 & 0.5984 & - 9.3444 & 6.5321 \\\text { Tickets } & 243.4401 & 43.2470 & 5.6291 & 0.0001 & 111.3406 & 375.5396 \\\hline\end{array}
-Referring to Scenario 14-10, the 99% confidence interval for the change in mean insurance
premiums of a person who has become 1 year older (i.e., the slope coefficient for AGE) is
-1.4061 ± _______.


Definitions:

Accounts Receivable

Money owed to a company by its customers for products or services that have been delivered but not yet paid for.

Deductions

Items of expenditure that the tax code allows taxpayers to deduct from income to arrive at taxable income.

Taxable Income

The portion of an individual's or company's income used as a base to calculate the amount of tax owed to the government.

Dependency Exemption

A tax exemption for taxpayers who support dependents who cannot fully support themselves.

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