1. This scatterplot is based on data points that have a correlation of r =.91.

Which assessment of the fit of the linear model is the most appropriate?

a. The pattern in the residual plot suggests that predictions based on the linear regression line will result in greater error as we move from left to right through the range of the explanatory variable.
b. The linear model is not appropriate because there is a distinctive curvilinear pattern in the residual plot.
c.
The linear model is appropriate because there is no pattern in the residual plot.

2. Movie data: We collected data from IMDb.com on 70 movies listed in the top 100 US box office sales of all time. These are the variable descriptions:

Metascore: Score out of 100, based on major critic reviews as provided by Metacritic.com

Total US box office sales: Total box office sales in millions of dollars

Rotten Tomatoes: Score out of 100, based on authors from writing guilds or film critic associations

We used Metascore ratings as an explanatory variable and Rotten Tomato ratings as the response variable in a linear regression. The se value is 11. With US box office sales as the explanatory variable and Rotten Tomato ratings as the response variable in a linear regression, the se value is 22. Using the se value, which is a better predictor of a movie’s Rotten Tomatoes score: Metascore or total US box office sales?

a. Total US box office sales
b. Metascore