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

question 47

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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 interpretation for the coefficient of determination? A) 74.67% of the variation in revenue can be explained by the variation in the number of downloads. B) 75.54% of the variation in revenue can be explained by the variation in the number of downloads. C) 74.67% of the variation in the number of downloads can be explained by the variation in revenue. D) 75.54% of the variation in the number of downloads can be explained by the variation in revenue.  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}{\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}

 ANOVA \text { ANOVA }
 df  SS  MS F Significance F Regression 1171062.9193171062.919386.47590.0000 Residual 2855388.43091978.1582 Total 29226451.3503\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 interpretation for the coefficient of determination? A) 74.67% of the variation in revenue can be explained by the variation in the number of downloads. B) 75.54% of the variation in revenue can be explained by the variation in the number of downloads. C) 74.67% of the variation in the number of downloads can be explained by the variation in revenue. D) 75.54% of the variation in the number of downloads can be explained by the variation in revenue.


 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 interpretation for the coefficient of determination? A) 74.67% of the variation in revenue can be explained by the variation in the number of downloads. B) 75.54% of the variation in revenue can be explained by the variation in the number of downloads. C) 74.67% of the variation in the number of downloads can be explained by the variation in revenue. D) 75.54% of the variation in the number of downloads can be explained by the variation in revenue. 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 interpretation for the coefficient of determination? A) 74.67% of the variation in revenue can be explained by the variation in the number of downloads. B) 75.54% of the variation in revenue can be explained by the variation in the number of downloads. C) 74.67% of the variation in the number of downloads can be explained by the variation in revenue. D) 75.54% of the variation in the number of downloads can be explained by the variation in revenue.
-Referring to Scenario 12-11, which of the following is the correct interpretation for the coefficient of determination?


Definitions:

Experimental Method

A research method involving the manipulation of variables to test hypotheses and determine cause-and-effect relationships in a controlled environment.

Psychometric Approach

A method in psychology focused on the measurement of mental functions, personality, and behavioural traits through standardized tests and assessments.

Representative Sample

A sample that accurately reflects the characteristics of the population from which it is drawn.

Survey

A method of gathering information from a sample of individuals, often used to collect data on opinions, behaviors, or characteristics.

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