This case study is comprised of a sample of one hundred movies with the following four variables: opening gross sales, total gross sales, number of theaters, and weeks in top 60. The four variables are used to analyze the motion picture industry, and show the descriptive statistic of the variables and to analyze the results. The results will show the high performance outliers of the motion picture industry and why. The correlation between total gross sales and each variable will be shown and will be accompanied by X, Y scatter graphs.

At completion of this case study the reader will understand the following descriptive statistics mean, standard deviation, sample deviation, and range for all four variables, and the correlation between total gross sales and each variable. Opening gross sales is the first variable; there is a huge gap between the highest value of 108. 44 and the lowest value of 0. 01 (Millions). This gap can be attributed to consumer’s reaction to advertisements of the movie.

This higher the value the more excited consumers are to watch the movie due to popularity or successful advertising, however the lower the number the less a consumer is excited to watch the movie which could be because of poor marketing or could simple be a bad movie. * The first descriptive statistic is the mean which is the average value of opening gross sales. The mean of opening gross sales is 9. 37432; this means that the average opening gross sales for a movie is over nine million dollars. This statistic could be used to assess the success of a particular movie compared to the mean. The next descriptive statistic to look at is standard deviation which shows the amount of dispersion from the mean.

The standard deviation for opening gross sales is 18. 8747, this shows that there is a deviation of over eighteen million dollars compared to the mean of the movie industry. * The third descriptive statistic is sample variance which shows the dispersion of numbers within a set of sample data. The sample variance for opening gross sales is 356. 2544; this shows the huge variance between the movies, this relates to popularity of movies and the two extremes of successful and unsuccessful movies. The last descriptive statistic is the range which is the difference between two extremes. The range for opening gross sales is 108. 427; the range continues to show the highs and lows of the movie industry as the minimum value for the movies is so low it hardly affects the maximum number.

The second variable is total gross sales this is similar to opening gross sales because there is a very big difference between the best selling movie and the least selling movie once again due to popularity. However some movies that did not have the best opening sales have ended with better total sales. The mean for total gross sales is 33. 0384, this shows that the average total movie sales is over thirty three million dollars. The movie industry would use this to see if there movies was above or below the industry average of thirty three million. * The standard deviation for total gross sales is 63. 16469269, this show that there is a sixty three million dollar deviation between the mean. * The sample variance for total gross sales is 3989. 778403, just like opening gross sales there is a large variance.

This is because of huge difference between successful and unsuccessful movies. * The range of total gross sales is 380. 151; once again the range is very high due to the lowest number being very small in comparison, which can be characterized as an unsuccessful movie. The third variable is number of theatres this variable shows how many movie theatres each particular movie is being shown in. This number will be based on not only the popularity of the movie but also the expected traffic of the movie. * The mean of the number of theatres is 1277. 4, this is the average number of theatres the movies are shown in. * The standard deviation of the number of theatres is 1378. 689 this shows the deviation from the mean which is because of some movies that are shown in a large amount of theatres and some movies are only shown in a few movie theatres.

* The sample variance for the number of theatres is 1900785, this can be also attributed to the popularity of movies some being very popular and shown in a large amount of theatres and some less popular and only being shown in a few movie theatres. The range of the number of theatres is 3905, once again the lowest value is very low and hardly effects the highest value. So this shows the difference between the movies that are shown in the most theatres and the movies that are shown in the least theatres. The fourth variable is number of weeks in top 60; this variable shows the level of popularity of the movie and how long it remained in the top 60 most popular movies. This variable has the least correlation with total gross sales.

* The mean of number of weeks in top 60 is 8. 8, which means the average amount of time a movie spends in the top 60 which would round up to nine weeks, if a movie spent less than nine weeks in the top 60 it would be considered as below average and if it was above nine weeks it would be considered as above average. * The standard deviation of number of weeks in top 60 is 6. 389511608 this shows a dispersion of six from the mean. * The sample variance of number of weeks in top 60 is 40. 82585859; the variance is the smallest of all the variables because the numbers are much lower.

In today’s movie industry it is difficult for a movie to stay in the top 60 because of the intense competition. * Then range of number of weeks in top 60 is 26, again this is the lowest number because of how difficult it is to stay in the top 60 for a prolonged period. The movies I think should be considered as high performance outliers are Star Wars: Episode III, and Harry Potter and the Goblet of Fire. Star Wars: Episode III is a high performance outlier because it excels in all categories such as total gross sales, opening gross sales, and weeks in top 60.

Harry potter and the Goblet of Fire is also a High performance outlier because it is a close second to Star Wars, as it also performs well in opening gross sales, total gross sales, and weeks in top 60. The correlation between total gross sales and opening gross sales is 0. 964251784 which means that they highly related to each other. This means that a movie that does well in opening gross sales is highly likely to do well in total gross sales. The correlation between total gross sales and number of theatres is 0. 09858186 this means that they have an above average correlation so the higher a movies total gross sales the more movie theatres it will generally be shown in.

The correlation between total gross sales and weeks in top 60 is 0. 525394855 this is the lowest correlation and shows that some movie that do not necessarily have a high total gross sales are still able to stay in the top 60, for a long period of time such as “The Wild parrots of Telegraph Hill” this movie had low total gross sale of 2. 1 but still managed to stay in the top 60 for longest period of time 27 weeks, for the most part total gross sales and weeks in top 60 are unrelated. This case study has been based on a sample of 100 movies and has shown the descriptive statistic for each variable, the relationships between the variables, and the correlation between total gross sales and each other variable. Throughout the case study there is a direct relationship between the movie’s opening gross sales and the overall success of the movie.