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

Question 104

Multiple Choice

SCENARIO 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:
$SCENARIO 12-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware.Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed: \begin{array}{lr} {\text { Regression Statistics }} \\ \hline \text { Multiple R } & 0.8691 \\ \hline \text { R Square } & 0.7554 \\ \hline \text { Adjusted R Square } & 0.7467 \\ \hline \text { Standard Error } & 44.4765 \\ \hline \text { Observations } & 30.0000 \\ \hline \end{array} \text { ANOVA } \begin{array}{|l|r|r|r|r|r|} \hline &\text { df } & \text { SS } & \text { MS } & F & \text { Significance } F \\ \hline \text { Regression } & 1 & 171062.9193 & 171062.9193 & 86.4759 & 0.0000 \\ \hline \text { Residual } & 28 & 55388.4309 & 1978.1582 & & \\ \hline \text { Total } & 29 & 226451.3503 & & \\ \hline \end{array} Simple Linear Regression 12-41 -Referring to Scenario 12-11, which of the following is the correct null hypothesis for testing whether there is a linear relationship between revenue and the number of downloads? A) H _ { 0 } : b _ { 1 } = 0 B) H _ { 0 } : b _ { 1 } \neq 0 C) H _ { 0 } : \beta _ { 1 } = 0 D) H _ { 0 } : \beta _ { 1 } \neq 0$ $\begin{array}{lr}{\text { Regression Statistics }} \\\hline \text { Multiple R } & 0.8691 \\\hline \text { R Square } & 0.7554 \\\hline \text { Adjusted R Square } & 0.7467 \\\hline \text { Standard Error } & 44.4765 \\\hline \text { Observations } & 30.0000 \\\hline\end{array}$

$\text { ANOVA }$
$\begin{array}{|l|r|r|r|r|r|}\hline &\text { df } & \text { SS } & \text { MS } & F & \text { Significance } F \\ \hline \text { Regression } & 1 & 171062.9193 & 171062.9193 & 86.4759 & 0.0000 \\\hline \text { Residual } & 28 & 55388.4309 & 1978.1582 & & \\\hline \text { Total } & 29 & 226451.3503 & & \\\hline\end{array}$

$SCENARIO 12-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware.Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed: \begin{array}{lr} {\text { Regression Statistics }} \\ \hline \text { Multiple R } & 0.8691 \\ \hline \text { R Square } & 0.7554 \\ \hline \text { Adjusted R Square } & 0.7467 \\ \hline \text { Standard Error } & 44.4765 \\ \hline \text { Observations } & 30.0000 \\ \hline \end{array} \text { ANOVA } \begin{array}{|l|r|r|r|r|r|} \hline &\text { df } & \text { SS } & \text { MS } & F & \text { Significance } F \\ \hline \text { Regression } & 1 & 171062.9193 & 171062.9193 & 86.4759 & 0.0000 \\ \hline \text { Residual } & 28 & 55388.4309 & 1978.1582 & & \\ \hline \text { Total } & 29 & 226451.3503 & & \\ \hline \end{array} Simple Linear Regression 12-41 -Referring to Scenario 12-11, which of the following is the correct null hypothesis for testing whether there is a linear relationship between revenue and the number of downloads? A) H _ { 0 } : b _ { 1 } = 0 B) H _ { 0 } : b _ { 1 } \neq 0 C) H _ { 0 } : \beta _ { 1 } = 0 D) H _ { 0 } : \beta _ { 1 } \neq 0$

$SCENARIO 12-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware.Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed: \begin{array}{lr} {\text { Regression Statistics }} \\ \hline \text { Multiple R } & 0.8691 \\ \hline \text { R Square } & 0.7554 \\ \hline \text { Adjusted R Square } & 0.7467 \\ \hline \text { Standard Error } & 44.4765 \\ \hline \text { Observations } & 30.0000 \\ \hline \end{array} \text { ANOVA } \begin{array}{|l|r|r|r|r|r|} \hline &\text { df } & \text { SS } & \text { MS } & F & \text { Significance } F \\ \hline \text { Regression } & 1 & 171062.9193 & 171062.9193 & 86.4759 & 0.0000 \\ \hline \text { Residual } & 28 & 55388.4309 & 1978.1582 & & \\ \hline \text { Total } & 29 & 226451.3503 & & \\ \hline \end{array} Simple Linear Regression 12-41 -Referring to Scenario 12-11, which of the following is the correct null hypothesis for testing whether there is a linear relationship between revenue and the number of downloads? A) H _ { 0 } : b _ { 1 } = 0 B) H _ { 0 } : b _ { 1 } \neq 0 C) H _ { 0 } : \beta _ { 1 } = 0 D) H _ { 0 } : \beta _ { 1 } \neq 0$ Simple Linear Regression 12-41 $SCENARIO 12-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware.Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed: \begin{array}{lr} {\text { Regression Statistics }} \\ \hline \text { Multiple R } & 0.8691 \\ \hline \text { R Square } & 0.7554 \\ \hline \text { Adjusted R Square } & 0.7467 \\ \hline \text { Standard Error } & 44.4765 \\ \hline \text { Observations } & 30.0000 \\ \hline \end{array} \text { ANOVA } \begin{array}{|l|r|r|r|r|r|} \hline &\text { df } & \text { SS } & \text { MS } & F & \text { Significance } F \\ \hline \text { Regression } & 1 & 171062.9193 & 171062.9193 & 86.4759 & 0.0000 \\ \hline \text { Residual } & 28 & 55388.4309 & 1978.1582 & & \\ \hline \text { Total } & 29 & 226451.3503 & & \\ \hline \end{array} Simple Linear Regression 12-41 -Referring to Scenario 12-11, which of the following is the correct null hypothesis for testing whether there is a linear relationship between revenue and the number of downloads? A) H _ { 0 } : b _ { 1 } = 0 B) H _ { 0 } : b _ { 1 } \neq 0 C) H _ { 0 } : \beta _ { 1 } = 0 D) H _ { 0 } : \beta _ { 1 } \neq 0$
-Referring to Scenario 12-11, which of the following is the correct null hypothesis for testing whether there is a linear relationship between revenue and the number of downloads?

A) $H _ { 0 } : b _ { 1 } = 0$
B) $H _ { 0 } : b _ { 1 } \neq 0$
C) $H _ { 0 } : \beta _ { 1 } = 0$
D) $H _ { 0 } : \beta _ { 1 } \neq 0$

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

Multiple Choice

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

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