Question $13$

$5$ pts

What does the regression output tell us about what predicts the number of user ratings on the movie website Fresh Tomatoes?

It tells us that # Theaters Total, Opening Weekend Revenues, and # Theaters Opening

Weekend predict the number of user ratings.

It tells us that the Tomatometer predicts the number of user ratings.

Nothing because the # Ratings is correlated with the # Theaters Total.

Nothing because this model tells us what predicts total revenues for movies.

Question $14$

$5$ pts

Of the following, which is the correct interpretation of this output?

A movie needs to open in at least $44$ theaters to make it to the top $50$ in revenues for the year.

Although some of the independent variables are statistically significantly predictors of the dependent variable, the whole model does not significantly predict total revenues.

The studio should increase the number of theaters a movie opens in to increase the total revenue of the movie.

Holding the other variables fixed, more theaters in opening weekend predict lower revenues.

Use this information for the next two questions.

The image below shows regression output from the Analysis Toolpak for an analysis of movie revenues. The regression analyzed the $50$ movies introduced in a single year that had the highest revenues. The dependent variable in the analysis is total revenues, in dollars, for the movie.

The "Tomatometer" is the rating from the movie website Fresh Tomatoes. The $"$# Ratings" is the number of user ratings on Fresh Tomatoes.

$\backslash$table$[[$Regression Statistics,,,,$],[$Multiple R$,0\mathrm{.}906,,,,],[$R Square,$0\mathrm{.}821,,,,],[$Adjusted R Square,$0\mathrm{.}801,,,,],[$Standard Error,$31545370\mathrm{.}1,,,,],[$Observations$,50,,,,],[$ANOVA$],[,,,,,$Significan$],[,df,$SS$,$MS$,F,$ceF