A box office analyst seeks to predict opening weekend box office gross for movies. Toward this goal, the analyst plans to use online trailer views as a predictor. For each of the 66 movies, the number of online trailer views from the release of the trailer through the Saturday before a movie opens and the opening weekend box office gross (in millions of dollars) are collected and stored in the accompanying table. A linear regression was performed on this data, and the result is the linear regression equation Ŷ₁ = -0.875 +1.3914X. Complete parts (a) through (c) below. Click on the icon to view the data table. a. Determine the coefficient of determination, 22, and interpret its meaning. 2= (Round to three decimal places as needed.) Interpret the meaning of r². The value of r² indicates that ☐ % of the variation in (Round to one decimal place as needed.) b. Determine the standard error of the estimate. Syx (Round to two decimal places as needed.) can be explained by the variation in c. How useful do you think this regression model is for predicting movie weekend box office gross? A. It is not useful for predicting box office gross because the coefficient of determination is close to 0. B. It is not useful for predicting box office gross because the coefficient of determination is close to 1. OC. It is very useful for predicting box office gross because the coefficient of determination is very close to 1.

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A box office analyst seeks to predict opening weekend box office gross for movies. Toward this goal, the analyst plans to use online trailer views as a predictor. For each of the 66 movies,
the number of online trailer views from the release of the trailer through the Saturday before a movie opens and the opening weekend box office gross (in millions of dollars) are collected
and stored in the accompanying table. A linear regression was performed on this data, and the result is the linear regression equation Ŷ₁ = -0.875 +1.3914X. Complete parts (a)
through (c) below.
Click on the icon to view the data table.
a. Determine the coefficient of determination, 22, and interpret its meaning.
2=
(Round to three decimal places as needed.)
Interpret the meaning of r².
The value of r² indicates that ☐ % of the variation in
(Round to one decimal place as needed.)
b. Determine the standard error of the estimate.
Syx
(Round to two decimal places as needed.)
can be explained by the variation in
c. How useful do you think this regression model is for predicting movie weekend box office gross?
A. It is not useful for predicting box office gross because the coefficient of determination is close to 0.
B. It is not useful for predicting box office gross because the coefficient of determination is close to 1.
OC. It is very useful for predicting box office gross because the coefficient of determination is very close to 1.
Transcribed Image Text:A box office analyst seeks to predict opening weekend box office gross for movies. Toward this goal, the analyst plans to use online trailer views as a predictor. For each of the 66 movies, the number of online trailer views from the release of the trailer through the Saturday before a movie opens and the opening weekend box office gross (in millions of dollars) are collected and stored in the accompanying table. A linear regression was performed on this data, and the result is the linear regression equation Ŷ₁ = -0.875 +1.3914X. Complete parts (a) through (c) below. Click on the icon to view the data table. a. Determine the coefficient of determination, 22, and interpret its meaning. 2= (Round to three decimal places as needed.) Interpret the meaning of r². The value of r² indicates that ☐ % of the variation in (Round to one decimal place as needed.) b. Determine the standard error of the estimate. Syx (Round to two decimal places as needed.) can be explained by the variation in c. How useful do you think this regression model is for predicting movie weekend box office gross? A. It is not useful for predicting box office gross because the coefficient of determination is close to 0. B. It is not useful for predicting box office gross because the coefficient of determination is close to 1. OC. It is very useful for predicting box office gross because the coefficient of determination is very close to 1.
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