TABLE 13- 11 a Company That Has the Distribution RightsANOVA-Referring to Table 13-11, Which of the Following Is the to Home

The Answer of TABLE 13- 11 a Company That Has the Distribution RightsANOVA-Referring to Table 13-11, Which of the Following Is the to Home

TABLE 13- 11 a Company That Has the Distribution RightsANOVA-Referring to Table 13-11, Which of the Following Is the to Home

The Answer of TABLE 13- 11 a Company That Has the Distribution RightsANOVA-Referring to Table 13-11, Which of the Following Is the to Home

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TABLE 13- 11
a Company That Has the Distribution Rights

question 125

Multiple Choice

TABLE 13- 11
A company that has the distribution rights to home video sales of previously released movies would like to use the box office gross (in millions of dollars) to estimate the number of units (in thousands of units) that it can expect to sell. 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 movie titles:
$\begin{array}{l}\text { Regression Statistics }\\\begin{array} { l c } \hline \text { Multiple R } & 0.8531 \\\text { RSquare } & 0.7278 \\\text { Adjusted R Square } & 0.7180 \\\text { Standard Error } & 47.8668 \\\text { Observations } & 30\end{array}\end{array}$
ANOVA
$\begin{array}{lrrrrr}\hline &\text { d f}& \text { SS } & \text { MS } & \text {F }& \text {Significance F} \\\hline \text {Regression }& 1 & 171499.78 & 171499.78 & 74.8505 & 2.1259E-09 \\\text {Residual} & 28 & 64154.42 & 2291.23 & & \\\text {Total} & 29 & 235654.20 & & & \\\hline\end{array}$

$\begin{array}{lrrrrrr}\hline & \text {Coefficients }& \text { Standard Error}& \text { t Stat }& \text { p -value }& \text {Lower 95\% }& \text {Upper 95\% }\\\hline \text { Intercept }& 76.5351 & 11.8318 & 6.4686 & 5.24 \mathrm{E}-07& 52.2987 & 100.7716 \\ \text {Gross} & 4.3331 & 0.5008 & 8.6516 & 2.13 \mathrm{E}-09 & 3.3072 & 5.3590 \\\hline\end{array}$

$TABLE 13- 11 A company that has the distribution rights to home video sales of previously released movies would like to use the box office gross (in millions of dollars) to estimate the number of units (in thousands of units) that it can expect to sell. 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 movie titles: \begin{array}{l} \text { Regression Statistics }\\ \begin{array} { l c } \hline \text { Multiple R } & 0.8531 \\ \text { RSquare } & 0.7278 \\ \text { Adjusted R Square } & 0.7180 \\ \text { Standard Error } & 47.8668 \\ \text { Observations } & 30 \end{array} \end{array} ANOVA \begin{array}{lrrrrr} \hline &\text { d f}& \text { SS } & \text { MS } & \text {F }& \text {Significance F} \\ \hline \text {Regression }& 1 & 171499.78 & 171499.78 & 74.8505 & 2.1259E-09 \\ \text {Residual} & 28 & 64154.42 & 2291.23 & & \\ \text {Total} & 29 & 235654.20 & & & \\ \hline\end{array} \begin{array}{lrrrrrr} \hline & \text {Coefficients }& \text { Standard Error}& \text { t Stat }& \text { p -value }& \text {Lower 95\% }& \text {Upper 95\% }\\ \hline \text { Intercept }& 76.5351 & 11.8318 & 6.4686 & 5.24 \mathrm{E}-07& 52.2987 & 100.7716 \\ \text {Gross} & 4.3331 & 0.5008 & 8.6516 & 2.13 \mathrm{E}-09 & 3.3072 & 5.3590 \\ \hline \end{array} -Referring to Table 13-11, which of the following is the correct interpretation for the slope coefficient? A) For each increase of 1 dollar in box office gross, expected home video units sold are estimated to increase by 4.3331 thousand units. B) For each increase of 1 million dollars in box office gross, expected home video units sold are estimated to increase by 4.3331 units. C) For each increase of 1 dollar in box office gross, expected home video units sold are estimated to increase by 4.3331 units. D) For each increase of 1 million dollars in box office gross, expected home video units sold are estimated to increase by 4.3331 thousand units.$ $TABLE 13- 11 A company that has the distribution rights to home video sales of previously released movies would like to use the box office gross (in millions of dollars) to estimate the number of units (in thousands of units) that it can expect to sell. 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 movie titles: \begin{array}{l} \text { Regression Statistics }\\ \begin{array} { l c } \hline \text { Multiple R } & 0.8531 \\ \text { RSquare } & 0.7278 \\ \text { Adjusted R Square } & 0.7180 \\ \text { Standard Error } & 47.8668 \\ \text { Observations } & 30 \end{array} \end{array} ANOVA \begin{array}{lrrrrr} \hline &\text { d f}& \text { SS } & \text { MS } & \text {F }& \text {Significance F} \\ \hline \text {Regression }& 1 & 171499.78 & 171499.78 & 74.8505 & 2.1259E-09 \\ \text {Residual} & 28 & 64154.42 & 2291.23 & & \\ \text {Total} & 29 & 235654.20 & & & \\ \hline\end{array} \begin{array}{lrrrrrr} \hline & \text {Coefficients }& \text { Standard Error}& \text { t Stat }& \text { p -value }& \text {Lower 95\% }& \text {Upper 95\% }\\ \hline \text { Intercept }& 76.5351 & 11.8318 & 6.4686 & 5.24 \mathrm{E}-07& 52.2987 & 100.7716 \\ \text {Gross} & 4.3331 & 0.5008 & 8.6516 & 2.13 \mathrm{E}-09 & 3.3072 & 5.3590 \\ \hline \end{array} -Referring to Table 13-11, which of the following is the correct interpretation for the slope coefficient? A) For each increase of 1 dollar in box office gross, expected home video units sold are estimated to increase by 4.3331 thousand units. B) For each increase of 1 million dollars in box office gross, expected home video units sold are estimated to increase by 4.3331 units. C) For each increase of 1 dollar in box office gross, expected home video units sold are estimated to increase by 4.3331 units. D) For each increase of 1 million dollars in box office gross, expected home video units sold are estimated to increase by 4.3331 thousand units.$
-Referring to Table 13-11, which of the following is the correct interpretation for the slope coefficient?

Definitions:

Encumbrance

A claim against a property by a party that is not the owner, often impacting the property’s use or transfer until the encumbrance is lifted.

Eligibility Requirements

Criteria that must be met in order to qualify for a specific program, service, or status.

Nonexchange Transactions

Transactions where an entity receives value without directly giving or promising equivalent value in exchange.

Reimbursement

Compensation paid to someone for out-of-pocket expenses they have incurred.