The data is collected to find out the mean, variance and mode of revenue passenger miles and load factor. The value of mean of passenger miles is representing that the company is progressing due to the increasing revenues. The value of variance shows that the revenues earned have much variation and the company generates different amount of revenues. The range for the data of revenue passenger miles is higher due to the gap between the minimum and maximum value. There is no mode in the data that shows that the revenues are different from each other .
The mean of the load factor is higher than the industry that shows that the company has significant influence over the industry. The value of variance shows that there is high variation in the load factor as compared to the industry. The range for the data of load factor is lower due to the gap between the minimum and maximum value. The value of mode shows that there are multiple repeated values in the data that shows consistence in the load factor of the company (Delta Airlines).
The scatterplot shows that the load factor and the revenue passenger miles for the company have weak correlation. The weakness is due to the significant load factor and low revenue passenger miles. The industry has a positive strong correlation between the two variables. The strength shows that the industry relies on both revenue passenger miles and load factor .
The findings show that the company is not performing well as compared to the industry. The company has to focus on revenue passenger miles as the overall industry has strong positive relationship between the two variables.
Reference
Maindonald, J., & Braun, W. J. (2010). Data Analysis and Graphics Using R: An Example-Based Approach. Cambridge: Cambridge University Press.
