Multiple Regression Models Case Study: Web
Video on Demand
Web Video on Demand (WVOD) is an Internet video-on-demand streaming service. The
company offers a subscription service for $5.99/month, which includes access to all
programming and 30-second commercial intervals.
In the last year, the company has recently begun producing its own programming, including 30-,
60-, and 120-minute television shows, specials, and films. Programming has been developed for
teen audiences as well as adults.
The following data represent the amount of money brought in through advertising sales, the
average number of viewers, length of the program, and the average viewer age per program.
Average # of
Length of Program
Average Viewer Age
The WVOD executives are in the process of evaluating a partnership with several independent
filmmakers to fund and distribute socially conscious and diverse programming. The executives
have asked for regression models to be developed based on specific needs. The three regression
model requests and programming details are included below.
The WVOD executives would like to see a regression model that predicts the amount of
advertising sales based on the number of viewers and the length of the program. Develop this
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regression model (“Regression Model A”). Web Video on Demand would like to acquire a 60minute documentary special about social media and bullying. The special is aimed at teen
viewers and is estimated to bring in 3.2 million viewers. Based on the regression model, predict
the advertising sales that could be generated by the special.
The WVOD executives would also like to see a regression model that predicts the amount of
advertising sales based on the number of viewers, the length of the program, and the average
viewer age. Develop this regression model (“Regression Model B”). Web Video on Demand
may acquire a 2-hour film that was a hit with critics and audiences at several international film
festivals. Initial customer surveys indicate that the film could bring in 14.1 viewers and the
average viewer age would be 32. Use this information to predict the advertising sales.
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