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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:

CPI

A gauge for inflation, the Consumer Price Index analyzes the weighted average price of a collection of consumer products and services.

GDP Deflator

An index that measures the prices of all new, domestically manufactured, final goods and services in a country's economy.

Ghent Altarpiece

A highly detailed polyptych altarpiece by Hubert and Jan van Eyck, renowned for its sophisticated technique and symbolism.

Hubert

Likely a reference to Hubert van Eyck, an Early Netherlandish painter and older brother of Jan van Eyck, thought to be a master of oil painting technique and detailed landscapes.

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