This case study shall be our final project. Please answer all questions from 1-12 for full credit. This is individual work, NOT group work. Predicting Movie Revenue Nash Information Services provides information and analytical services to the movie indust

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This case study shall be our final project. Please answer all questions from 1-12 for full credit. This is individual work, NOT group work. Predicting Movie Revenue Nash Information Services provides information and analytical services to the movie industry, including statistical models for predicting movie revenue. Consider a random sample of 40 movies released over a five-year period. This sample was collected to see if information available soon after the theatrical release can successfully predict total box office revenue. The population of interest is much larger and consists of all movies released over this five-year period. Consider that the response variable is a movie’s total U.S. box office revenue (USRevenue). Among the explanatory variables are the movie’s budget (Budget), opening-weekend revenue (Opening), how many theaters the movie was in for the opening weekend (Theaters), and Ratings (e.g. Rating 1). All dollar amounts are measured in millions of U.S. dollars. The data file is “boxoffice.csv”. You can use the following R command to load the data from your local device to R


1. Preliminary analysis. 

(a) (0.5 points) The response variable (USRevenue) is quantitative. How about the explanatory variables? Which of the explanatory variables are quantitative? which categorical? 

(b) (1 points) Consider three (quantitative) explanatory variables: Budget, Opening and Theater. Use scatterplot to study the relationship between the response variable and each of these 3 explanatory variables. Comment. 

(c) (1 points) Provide correlation matrix among four variables, Budget, Opening, Theaters, and USRevenue. Is each quantitative explanatory variable highly correlated with the response variable? are explanatory variables highly correlated with themselves? 


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