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

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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, ________ of the variation in Accel Time can be explained by the dummy variable Sedan while controlling for the other independent variable.


 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, ________ of the variation in Accel Time can be explained by the dummy variable Sedan while controlling for the other independent variable.
-Referring to Scenario 14-16, ________ of the variation in Accel Time can be explained by the
dummy variable Sedan while controlling for the other independent variable.


Definitions:

Output Producers

Businesses or individuals that create goods or services for consumption.

Aggregate Demand Curve

A graphical representation showing the total demand for goods and services within a particular economy at different price levels.

Goods and Services

The output of an economy that includes both physical products and intangible activities offered for consumption.

Coincident Economic Indicator

An economic statistic that changes at the same time as the economy or stock market, providing insight into the current state of economic activity.

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