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Instruction 12-11
a Computer Software Developer Would Like to Use

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Instruction 12-11
A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware.Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:
 Regression Statistics  Multiple R 0.8691 R Square 0.7554 Adjusted R Square 0.7467 Standard Error 44.4765 Observations 30.0000\begin{array}{lr}\hline {\text { Regression Statistics }} \\\hline \text { Multiple R } & 0.8691 \\\hline \text { R Square } & 0.7554 \\\hline \text { Adjusted R Square } & 0.7467 \\\text { Standard Error } & 44.4765 \\\text { Observations } & 30.0000 \\\hline\end{array}
ANOVA
df SS  MS F Significance F Regression 1171062.9193171062.919386.47590.0000 Residual 2855388.43091978.1582 Total 29226451.3503\begin{array}{lr|r|r|r|r}\hline & d f & {\text { SS }} &{\text { MS }} & F & \text { Significance } F \\\hline \text { Regression } & 1 & 171062.9193 & 171062.9193 & 86.4759 & 0.0000 \\\hline \text { Residual } & 28 & 55388.4309 & 1978.1582 & & \\\hline \text { Total } & 29 & 226451.3503 & & & \\\hline\end{array}

 Coefficients  Standard Emor t Stat  P-value  Lower 95%  Upper 95%  Intercept 95.061426.91833.53150.0015150.200939.9218 Download 3.72970.40119.29920.00002.90824.5513\begin{array}{lrrrrrrr}\hline & \text { Coefficients } & \text { Standard Emor } & t \text { Stat } & \text { P-value } & \text { Lower 95\% } & \text { Upper 95\% } \\\hline \text { Intercept } & -95.0614 & 26.9183 & -3.5315 & 0.0015 & -150.2009 & -39.9218 \\\text { Download } & 3.7297 & 0.4011 & 9.2992 & 0.0000 & 2.9082 & 4.5513 \\\hline\end{array}  Instruction 12-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware.Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:   \begin{array}{lr} \hline {\text { Regression Statistics }} \\ \hline \text { Multiple R } & 0.8691 \\ \hline \text { R Square } & 0.7554 \\ \hline \text { Adjusted R Square } & 0.7467 \\ \text { Standard Error } & 44.4765 \\ \text { Observations } & 30.0000 \\ \hline \end{array}  ANOVA   \begin{array}{lr|r|r|r|r} \hline & d f & {\text { SS }} &{\text { MS }} & F & \text { Significance } F \\ \hline \text { Regression } & 1 & 171062.9193 & 171062.9193 & 86.4759 & 0.0000 \\ \hline \text { Residual } & 28 & 55388.4309 & 1978.1582 & & \\ \hline \text { Total } & 29 & 226451.3503 & & & \\ \hline \end{array}    \begin{array}{lrrrrrrr} \hline & \text { Coefficients } & \text { Standard Emor } & t \text { Stat } & \text { P-value } & \text { Lower 95\% } & \text { Upper 95\% } \\ \hline \text { Intercept } & -95.0614 & 26.9183 & -3.5315 & 0.0015 & -150.2009 & -39.9218 \\ \text { Download } & 3.7297 & 0.4011 & 9.2992 & 0.0000 & 2.9082 & 4.5513 \\ \hline \end{array}      -Referring to Instruction 12-11,which of the following is the correct interpretation for the coefficient of determination? A) 72.8% of the variation in the video unit sales can be explained by the variation in the box office gross. B) 71.8% of the variation in the video unit sales can be explained by the variation in the box office gross. C) 71.8% of the variation in the box office gross can be explained by the variation in the video unit sales. D) 72.8% of the variation in the box office gross can be explained by the variation in the video unit sales.  Instruction 12-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware.Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:   \begin{array}{lr} \hline {\text { Regression Statistics }} \\ \hline \text { Multiple R } & 0.8691 \\ \hline \text { R Square } & 0.7554 \\ \hline \text { Adjusted R Square } & 0.7467 \\ \text { Standard Error } & 44.4765 \\ \text { Observations } & 30.0000 \\ \hline \end{array}  ANOVA   \begin{array}{lr|r|r|r|r} \hline & d f & {\text { SS }} &{\text { MS }} & F & \text { Significance } F \\ \hline \text { Regression } & 1 & 171062.9193 & 171062.9193 & 86.4759 & 0.0000 \\ \hline \text { Residual } & 28 & 55388.4309 & 1978.1582 & & \\ \hline \text { Total } & 29 & 226451.3503 & & & \\ \hline \end{array}    \begin{array}{lrrrrrrr} \hline & \text { Coefficients } & \text { Standard Emor } & t \text { Stat } & \text { P-value } & \text { Lower 95\% } & \text { Upper 95\% } \\ \hline \text { Intercept } & -95.0614 & 26.9183 & -3.5315 & 0.0015 & -150.2009 & -39.9218 \\ \text { Download } & 3.7297 & 0.4011 & 9.2992 & 0.0000 & 2.9082 & 4.5513 \\ \hline \end{array}      -Referring to Instruction 12-11,which of the following is the correct interpretation for the coefficient of determination? A) 72.8% of the variation in the video unit sales can be explained by the variation in the box office gross. B) 71.8% of the variation in the video unit sales can be explained by the variation in the box office gross. C) 71.8% of the variation in the box office gross can be explained by the variation in the video unit sales. D) 72.8% of the variation in the box office gross can be explained by the variation in the video unit sales.
-Referring to Instruction 12-11,which of the following is the correct interpretation for the coefficient of determination?


Definitions:

Issue Price

The price at which securities, such as bonds or shares, are originally sold to the public or investors by the issuing entity.

Installment Note Payable

A debt instrument that requires a series of periodic payments to the lender over a specified period of time.

Interest Expense

The expenditure an entity incurs from borrowing funds during a certain period.

Notes Payable

Written agreements in which one party promises to pay another party a definite sum of money either on demand or at a specified future date.

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