Hello, I am looking for someone to write an essay on Quantitative Analysis of Cinematic Statistics. It needs to be at least 1500 words.Download file to see previous pages... Table 1, Appendices A show

Hello, I am looking for someone to write an essay on Quantitative Analysis of Cinematic Statistics. It needs to be at least 1500 words.

Table 1, Appendices A shows total numerical values used for this analysis.

The related trend between cinemas and screens as shown in Chart 1 Appendices A is that the number of screens increased over time in correlation with the number of cinema sites. however, as cinema sites tapered off, screens maintained a slight increase. The index number inferences, shown in Index A and B, Appendices A, describe a relative increase for screens of 5.5 percent in 2004 based on 1994, but only 0.3 percent for cinemas. Admissions revenue based on 1994 delivered a price relative average increase of 3.8%, and based on 1999 the price relative was only 2.8% as related in Index C, Appendices A. Furthermore, Chart 2 Appendices A describes the relative increase of admission revenue which can be correlated to the amount of screen increase per cinema. This infers that the more screens per cinema, the higher revenue increase. This is a good indicator for management staff that more revenue is generated the higher the concentration of screens, and for the customers this allows more movie options in a singular location, further increasing admissions revenue.

Chart 3 Appendices A shows the sharp increase of admission revenue as cinemas increase, which induces the trend of a positive relationship. Using the linear regression equation y = 5.6951x - 3722.7, it can be derived that there is a trend of increase in admission revenue in relationship to cinemas sites. The correlation coefficient equals 0.877, which is a high value which infers a positive relationship between increase in admission revenue and cinema sites. The forecasted admission value for 2005 is 780.6082 m provided that 772 cinemas are built.

Admissions and Cinema Screens

Chart 4 Appendices A demonstrates a dramatic slope accession of admissions revenue as screens increase/ Linear equation Linear equation y = 7.3519x - 502.72 trends at a higher correlation between admission revenue and screens that noted in admissions and sites, the correlation coefficient with screens is 0.98486, intuitive of an impressive positive growth relationship between these factors. The forecast for admissions in relationship to screens in 2005 would be 25229.1m, provided that 3500 screens are built and the market can support that amount of cinematic screens, if 350 screens are built, the 2005 forecast would be 2070.45m, a more plausible plan of action.

Gross Box Office (GBO) and Cinema Sites

Chart 5 Appendices A plots the relationship between GBO and cinema sites, showing a sharp increase in GBO in relation to the increase in sites. The linear equation y = 0.0361x = 651.7 concludes to this positive relationship with a correlation coefficient of 0.892993 further demonstrates the solid positive increases in GBC as it relates to cinema sites. Forecasting for 2005 with 772 cinema sites-meaning that one cinema is inoperable-would bring a GBO of 3221.81 m, a slight decrease from 2004, but significant of the relationship between the number of cinemas and GBO.

Gross Box Office (GBO) and Cinema Screens

GBO and cinema screens also have a correlative relationship as visualised in Chart 5 Appendices A.