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SCENARIO 14-16
What Are the Factors That Determine the Acceleration YY

question 26

True/False

SCENARIO 14-16
What are the factors that determine the acceleration time (in sec.) from 0 to 60 miles per hour of a
car? Data on the following variables for 30 different vehicle models were collected: YY (Accel Time): Acceleration time in sec.
XIX _ { I } (Engine Size): c.c.
X2X _ { 2 } (Sedan): 1 if the vehicle model is a sedan and 0 otherwise

The regression results using acceleration time as the dependent variable and the remaining variables as the independent variables are presented below.

 Regression Statistics  Multiple R 0.6096 R Square 0.3716 Adjusted R Square 0.3251 Standard Error 1.4629 Observations 30\begin{array}{lr}\hline{\text { Regression Statistics }} \\\hline \text { Multiple R } & 0.6096 \\\text { R Square } & 0.3716 \\\text { Adjusted R Square } & 0.3251 \\\text { Standard Error } & 1.4629 \\\text { Observations } & 30 \\\hline\end{array}

ANOVA
 SCENARIO 14-16 What are the factors that determine the acceleration time (in sec.) from 0 to 60 miles per hour of a car? Data on the following variables for 30 different vehicle models were collected:  Y  (Accel Time): Acceleration time in sec.  X _ { I }  (Engine Size): c.c.  X _ { 2 }  (Sedan): 1 if the vehicle model is a sedan and 0 otherwise  The regression results using acceleration time as the dependent variable and the remaining variables as the independent variables are presented below.   \begin{array}{lr} \hline{\text { Regression Statistics }} \\ \hline \text { Multiple R } & 0.6096 \\ \text { R Square } & 0.3716 \\ \text { Adjusted R Square } & 0.3251 \\ \text { Standard Error } & 1.4629 \\ \text { Observations } & 30 \\ \hline \end{array}   ANOVA      \begin{array}{lrrrrrr} \hline & \text { Coefficients } & \text { Standard Error } & \text { t Stat } & \text { P-value } & \text { Lower 95\% } & \text { Upper 95\% } \\ \hline \text { Intercept } & 7.1052 & 0.6574 & 10.8086 & 0.0000 & 5.7564 & 8.4540 \\ \text { Engine Size } & -0.0005 & 0.0001 & -3.6477 & 0.0011 & -0.0008 & -0.0002 \\ \text { Sedan } & 0.7264 & 0.5564 & 1.3056 & 0.2027 & -0.4152 & 1.8681 \\ \hline \end{array}      -Referring to Scenario 14-16, there is enough evidence to conclude that being a sedan or not makes a significant contribution to the regression model in the presence of the other independent variable at a 5% level of significance.


 Coefficients  Standard Error  t Stat  P-value  Lower 95%  Upper 95%  Intercept 7.10520.657410.80860.00005.75648.4540 Engine Size 0.00050.00013.64770.00110.00080.0002 Sedan 0.72640.55641.30560.20270.41521.8681\begin{array}{lrrrrrr}\hline & \text { Coefficients } & \text { Standard Error } & \text { t Stat } & \text { P-value } & \text { Lower 95\% } & \text { Upper 95\% } \\\hline \text { Intercept } & 7.1052 & 0.6574 & 10.8086 & 0.0000 & 5.7564 & 8.4540 \\\text { Engine Size } & -0.0005 & 0.0001 & -3.6477 & 0.0011 & -0.0008 & -0.0002 \\\text { Sedan } & 0.7264 & 0.5564 & 1.3056 & 0.2027 & -0.4152 & 1.8681 \\\hline\end{array}

 SCENARIO 14-16 What are the factors that determine the acceleration time (in sec.) from 0 to 60 miles per hour of a car? Data on the following variables for 30 different vehicle models were collected:  Y  (Accel Time): Acceleration time in sec.  X _ { I }  (Engine Size): c.c.  X _ { 2 }  (Sedan): 1 if the vehicle model is a sedan and 0 otherwise  The regression results using acceleration time as the dependent variable and the remaining variables as the independent variables are presented below.   \begin{array}{lr} \hline{\text { Regression Statistics }} \\ \hline \text { Multiple R } & 0.6096 \\ \text { R Square } & 0.3716 \\ \text { Adjusted R Square } & 0.3251 \\ \text { Standard Error } & 1.4629 \\ \text { Observations } & 30 \\ \hline \end{array}   ANOVA      \begin{array}{lrrrrrr} \hline & \text { Coefficients } & \text { Standard Error } & \text { t Stat } & \text { P-value } & \text { Lower 95\% } & \text { Upper 95\% } \\ \hline \text { Intercept } & 7.1052 & 0.6574 & 10.8086 & 0.0000 & 5.7564 & 8.4540 \\ \text { Engine Size } & -0.0005 & 0.0001 & -3.6477 & 0.0011 & -0.0008 & -0.0002 \\ \text { Sedan } & 0.7264 & 0.5564 & 1.3056 & 0.2027 & -0.4152 & 1.8681 \\ \hline \end{array}      -Referring to Scenario 14-16, there is enough evidence to conclude that being a sedan or not makes a significant contribution to the regression model in the presence of the other independent variable at a 5% level of significance.
-Referring to Scenario 14-16, there is enough evidence to conclude that being a
sedan or not makes a significant contribution to the regression model in the presence of the other
independent variable at a 5% level of significance.


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