business

For this activity you will use the Chapter 3 Webfile Top50Movies.xlsx.

Data from fifty of the top box office receipt generating movies are provided in the file. Quantitative variables for the movie’s release year, inflation- and noninflations-adjusted box office receipts in the United States, budget and the world box office receipts are also included.

Use the data visualization methods presented in Chapter 3 to explore these data and discover relationships between the variables. Include the following in your report:

1. Create a scatter chart to examine the relationship between the year released and the inflation-adjusted U.S. box office receipts. Include a trendline. What does that chart indicate about U.S. inflations-adjusted receipts over time for these top 50 movies?

2. Create scatter chart to examine the relationship between the budget and the noninflation-adjusted world box office receipts. (Hint: You may need adjust the data to ignore the missing budget valeus to create your chart). What does this scatter chart indicate about the relationship between the movie’s budget and the world box office receipts?

3. Create a frequency distribution, percent frequency distribution, and histogram for the inflation-adjusted U.S. box office receipts. Use bin sizes of $100 million. Interpret the results. Do their appear to be any outliers?

4. Create a PivotTable for these data. Use the PivotTable to generate a crosstabulation for movie genre and rating. Determine which combinations of genre and rating are most represented in the top 50 movie data. Now filter the data to consider only movies after 1980. What combinations are most represented after 1980? What does this indicate about how the preferences of moviegoers have changed over time?

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