The data in Table 8.25 were collected in order to study factors affecting the supply and demand for commercial air travel. Data on various aspects of commercial air travel for an arbitrarily chosen set of 74 pairs of cities were obtained from a 1966 (before deregulation) CAB study. Other data were obtained from a standard atlas. The variables are:

(a) Perform a regression relating the number of passengers to the other variables. Check residuals for possible specification errors. Do the results make sense?

(b) Someone suggests using the logarithms of all variables for the regression. Does this recommendation make sense? Perform the regression using logarithms; answer all questions as in part (a).

(c) Another use of the data is to use the number of airlines as the dependent variable. What different aspect of the demand or supply of airline travel is related to this model? Implement that model and relate the results to those of parts (a) and (b). 

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CITY1 and CITY2: a pair of cities, PASS: the number of passengers flying between the cities in a sample week, MILES: air distance between the pair of cities, INM: per capita income in the larger city, INS: per capita income in the smaller city, POPM: population of the larger city, POPS: population of the smaller city, and AIRL: the number of airlines serving that route.