For the next exercise, you are going to use the Airline Costs dataset available to download from OA 8.4. The dataset has the following attributes, among others:

i. Airline name

ii. Length of flight in miles

iii. Speed of plane in miles per hour

iv. Daily flight time per plane in hours

v. Customers served in 1000s

vi. Total operating cost in cents per revenue ton-mile

vii. Total assets in $100,000s

viii. Investments and special funds in $100,000s Use a linear regression model to predict the number of customers each airline serves from its length of flight and daily flight time per plane. Next, build another regression model to predict the total assets of an airline from the customers served by the airline. Do you have any insight about the data from the last two regression models?