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In a Comprehensive Road Test for New Car Models, One yy

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Essay

In a comprehensive road test for new car models, one variable measured is the time it
takes the car to accelerate from 0 to 60 miles per hour. To model acceleration time, a
regression analysis is conducted on a random sample of 129 new cars. TIME60: yy = Elapsed time (in seconds) from 0mph0 \mathrm { mph } to 60mph60 \mathrm { mph }
MAX: x=x = Maximum speed attained (miles per hour)
The simple linear model E(y)=β0+β1xE ( y ) = \beta _ { 0 } + \beta _ { 1 } x was fit to the data. Computer printouts for the analysis are given below:
 PREDICTOR  VARIABLES  COEFFICIENT  STD ERROR  STUDENT’S T  P  CONSTANT 18.71710.6370829.380.0000 MAX 0.083650.0049117.050.0000\begin{array}{l|c|c|c|c}\text { PREDICTOR } & & & & \\\text { VARIABLES } & \text { COEFFICIENT } & \text { STD ERROR } & \text { STUDENT'S T } & \text { P } \\\hline \text { CONSTANT } & 18.7171 & 0.63708 & 29.38 & 0.0000 \\\text { MAX } & -0.08365 & 0.00491 & -17.05 & 0.0000\end{array}

 R-SQUARED 0.6960 RESID. MEAN SQUARE (MSE) 1.28695 ADJUSTED R-SQUARED 0.6937 STANDARD DEVIATION 1.13444\begin{array}{llll}\text { R-SQUARED } & 0.6960 & \text { RESID. MEAN SQUARE (MSE) } & 1.28695 \\\text { ADJUSTED R-SQUARED } & 0.6937 & \text { STANDARD DEVIATION } & 1.13444\end{array}

 In a comprehensive road test for new car models, one variable measured is the time it takes the car to accelerate from 0 to 60 miles per hour. To model acceleration time, a regression analysis is conducted on a random sample of 129 new cars. TIME60:  y  = Elapsed time (in seconds) from  0 \mathrm { mph }  to  60 \mathrm { mph }  MAX:  x =  Maximum speed attained (miles per hour) The simple linear model  E ( y ) = \beta _ { 0 } + \beta _ { 1 } x  was fit to the data. Computer printouts for the analysis are given below:  \begin{array}{l|c|c|c|c} \text { PREDICTOR } & & & & \\ \text { VARIABLES } & \text { COEFFICIENT } & \text { STD ERROR } & \text { STUDENT'S T } & \text { P } \\ \hline \text { CONSTANT } & 18.7171 & 0.63708 & 29.38 & 0.0000 \\ \text { MAX } & -0.08365 & 0.00491 & -17.05 & 0.0000 \end{array}    \begin{array}{llll} \text { R-SQUARED } & 0.6960 & \text { RESID. MEAN SQUARE (MSE) } & 1.28695 \\ \text { ADJUSTED R-SQUARED } & 0.6937 & \text { STANDARD DEVIATION } & 1.13444 \end{array}       CASES INCLUDED 129 MISSING CASES 0  \text { Find and interpret the estimate } \hat { \beta } 1 \text { in the printout above. }


CASES INCLUDED 129 MISSING CASES 0  Find and interpret the estimate β^1 in the printout above. \text { Find and interpret the estimate } \hat { \beta } 1 \text { in the printout above. }


Definitions:

Sales Commission

A reward or payment made to a salesperson, typically calculated as a percentage of the sales they have generated.

Incentive Systems

Arrangements used by organizations to motivate and reward employees for achieving specific performance targets.

Industrial Buyers

Individuals or organizations that purchase goods or services for industrial use, manufacturing, or for resale to other consumers.

Productivity Measurement

The process of quantifying the efficiency and effectiveness of production.

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