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SCENARIO 13-10
You Worked as an Intern at We Always

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SCENARIO 13-10
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 ANOVA df SS  MS  F  Siqnificonce F  Regression 2835284.650016.24570.0004 Residual 12616987.8200 Total 2287557.1200 Coefficients  Standard Error t Stat  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}\begin{array} { l r } \hline { \text { Regression 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 c c c c } & d f & \text { SS } & \text { MS } & \text { F } & \text { Siqnificonce F } \\\hline \text { Regression } & 2 & & 835284.6500 & 16.2457 & 0.0004 \\\text { Residual } & 12 & 616987.8200 & \\\text { Total } && 2287557.1200& & & \\\hline\end{array}\\\\\begin{array} { l r r r r r r } \hline & \text { Coefficients } & \text { Standard Error } & { t \text { Stat } } & \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}\end{array}
-Referring to SCENARIO 13-10, to test the significance of the multiple regression model, what is the form of the null hypothesis? a) H0:β1=0H _ { 0 } : \beta _ { 1 } = 0
b) H0:β2=0H _ { 0 } : \beta _ { 2 } = 0
c) H0:β1=β2=0H _ { 0 } : \beta _ { 1 } = \beta _ { 2 } = 0
d) H0:β0=β1=β2=0H _ { 0 } : \beta _ { 0 } = \beta _ { 1 } = \beta _ { 2 } = 0

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