Scenario: Why do some movies make more money at the box office than others? Hollywood is a multi-billion dollar industry which releases more than a hundred films a year, with large variations in the budgets and box office grosses of the movies. Identifying which factors are important to a movie's profitability and subsequently predicting the success of a movie given its relevant parameters could save movie studios hundreds of millions of dollars a year. Using a dataset containing information on 500 movies, your job is to construct a multiple regression to determine the characteristics of a movie that help predict success at the box office. The variables are as follows:

YiYi: Movie ii's box office revenue in millions of U.S. dollars (USD). This is only the domestic revenue received at U.S. theaters during the first run of the movie (i.e., no DVD sales, international revenue, etc.). The variable is in inflation adjusted terms so we can compare movie revenue without having to worry about changes in the price level.

X1iX1i: Production Budget of Movie ii in millions of USD.

X2iX2i: Critical review of Movie ii from Rotten Tomatoes (range: 0-100).

X3iX3i: Number of official trailer views in millions.

X4iX4i: Star Power of Movie ii. This is a relative measure that determines the overall caliber of movie stars in the cast. A high number for Star Power means that Movie ii has a cast containing a high number of famous actors. The average of this variable is 100, so if a movie has a star power rating of 120, then that means it is 20% above average.

X5iX5i: Established Audience of Movie ii. This is a variable that equals 1 if Movie ii is based off of a book or is a sequel to another movie (zero otherwise).

X6iX6i: Is Movie ii a Childrens' Movie? This is a variable that equals 1 if Movie ii is considered a childrens' movie (zero otherwise).