Application and Reasoning Problems

7.4. Consider two airports that are located near each other, such as the Buffalo International Airport (in Buffalo, NY) and the Rochester Airport (in Rochester, NY). Suppose you were to collect data from each airline at each airport as to what percentage of their flights arrive on time. Your data might look something like that in the data file C07 Airports.xls [.rda].

1. Would you expect the two variables to be strongly or weakly correlated? Explain your answers based on an analysis of the situation, not on the actual data.
2. If you said the correlation is strong, would it be positive or negative? Explain your answer. Is this relationship causal? In other words, do more on time arrivals at one airport cause more on-time arrivals at the other airport, or is it merely a coincidence that more on-time arrivals at one airport tend to be associated with more on-time arrivals at the other airport?
3. If you said they are weakly correlated, what other variable might you measure between the two airports that would be strongly correlated?
4. How do your predictions compare with the results from the actual data?

7.5. Review the reading at the beginning of this unit.

1. There are three terms (in bold italics) defined in this reading material. Which of these three terms means the same as the term ”explanatory variable”? Why might this be a useful description of that term?
2. There are three terms (in bold italics) defined in this reading material. Which of these three terms means the same as the term ”response variable”? Why might this be a useful description of that term?
3. The third paragraph gives an example of a relationship between the price you pay for an airline ticket and the distance being flown. Is this relationship represented by a function (as described and defined in the reading material)?