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Motion Picture Industry

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Lisa Cooper

CSU-Global Campus

Quantitative Business Analysis MTH410

Mod 2 Critical Thinking

Dr. Barry Smith

7/20/2011

The quantitative analysis of the Motion Picture Industry provided by the textbook with the data set reveals many key aspects of the industry. Utilizing the descriptive statistics for each of the four variables in the data set can include mean, mode, median, z-score, standard deviation, dispersion, and correlation coefficient. Outliers are defined as a data set that has unusually large or unusually small values will also be determined using the same statistics (Anderson, et al., 2011). An evaluation of these descriptive statistics and the relationship between the total gross sales will be the focus of this critical thinking exercise. Good introduction.

The first data set includes opening day gross revenues. The median opening day gross was .39 which means that half of the movies in this data set were less than .39 and the rest were more than .39. The median is the middle of an ordered score of an odd number of data or half way between the even two numbers. The mean was 9.38 and the standard deviation was 18.875 based on 100 movies (Expert, 2011). Simple mean is calculated with the follow formula: x=Ex1/n.The opening day variance is .03 to 108.44 ($ millions) equaling 108.43. Therefore with a median of .39 and a mean of 9.38 indicates that there are many movies on opening day that are not making money and a few are making much money.

(Expert, 2011)

The second set of data is the total gross revenue column. The data width or range is from .03 to 380.176 equaling 380.18 which is a large variance. The median total gross sales were 5.85% which is much higher than the opening day sales. The mean is 33.04 and the standard deviation is 63.165 based on the same 100 films. The histogram illustrates this data information

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