Refer to Exercise 12.12. In the plot of the data, airport 20 had a much larger revenue than any…
Refer to Exercise 12.12. In the plot of the data, airport 20 had a much larger revenue than any of the other 21 airports.
a. Replot the three scatterplots with the data from airport 20 deleted. Does there appear to be any relationship among revenue and the two explanatory variables in this data set?
b. Fit a first-order regression model relating revenue to distance and population size. Comment on the quality of the fit of the model to the data. Is revenue related to distance from hub and population size once airport 20 is deleted from the data?
c. What conclusions can be inferred from parts (a) and (b) about the importance of plotting the data and not just running models through a software program?
A regional airline transfers passengers from small airports to a larger regional hub airport. The airline’s data analyst was assigned to estimate the revenue (in thousands of dollars) generated by each of the 22 small airports based on two variables: the distance from each airport (in miles) to the hub and the population (in hundreds) of the cities in which each of the 22 airports is located. The data is given in the following table.
a. Produce three scatterplots: revenue versus distance, revenue versus population, and distance versus population.
b. For the 22 airports, is there a strong correlation between airport distance from the regional hub and city population?
c. Does there appear to a problem with high leverage points? Justify your answer.
d. Fit a first-order regression model relating revenue to distance and population size. Comment on the quality of the fit of the model to the data. e. Do the two estimated slopes appear to have the appropriate sign? If not, explain why.