This article talked about how different factors effect the amount of money that a movie will make. The article uses an equation that predicts the amount of money that a movie will make once it is released into the box office. The article uses the equation on an example movie and shows how accurate the equation was by comparing it to the actual amount of money that the movie made. The article concluded that there is a high correlation between positive review and the movie's success. Which is saying that if the movie gets good reviews from the critics, then the movie will have financial success. I found this article very interesting because I was interested in learning the different aspects of movies that make them more successful, such as if the movie is rated pg-13 and whether the movie is a part of a sequel. I also found interesting how different aspects gain more money and how much more money they gain from having those aspects. This article relates to what we are learning in class because it talks about things such as a linear regression model and the line of regression on a scatter plot. It then uses the line to form conclusions about the data that was collected. One new thing that I found in this article that we have not yet talked about in class was the term statistically significant. It referred to which variable actually effected the outcome of the box office gross.
Equation: Gross = –80 + 0.6×RT + 0.5×Budget + 0.025×Theaters + 50×Sequel + 20×PG13
The 2011 movie "Sherlock Holmes: A Game of Shadows"
Gross = -80 + 0.6x(60%) + 0.5x(175) + 0.025x(3600) + 50x(1) + 20x(1)
Predicted gross= $203,500,000
Actual gross= $186,848,418
The model was kind of accurate on estimating the domestic box office gross for this movie. It overestimated how much the movie would make by about 16,000,000.
The movie released within the next 3 months "Skyfall"
Gross = -80 + 0.6(100%) + 0.5x(150) + 0.025x(3000) + 50(1) + 20x(1)
Predicted gross = 200,000,000
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