An airline developed a regression model to predict revenue from ights that connect "feeder\" cities to its hub airport. The response in the model is the revenue generated by ights operating to the feeder cities (in thousands of dollars per month), and the two explanatory variables are the air distance between the hub and feeder city (Distance, in miles) and the population of the feeder city (in thousands). The least squares regression equation based on dam for 37 feeder locations last month is Estimated revenue = 86 + 0.2Distance +1.2Population with R2 = 0.75 and s3 = 32.6. Complete parts a through d. (a) The airline plans to expand its operations to add an additional feeder city. The rst possible city has population 125,000 and is 275 miles from the hub. A second possible city has population 100,000 and is 325 miles from the hub. Which would you recommend ifthe airline wants to increase total revenue? 0 The second city 0 The rst city