Scenario: Let’s look again at some airline delays data from Chicago. This time, we’ll consider a single week during March 2009, and focus on departure delays for United Airlines flights. There were more than 1,500 scheduled departures during the week. Fifty-eight were cancelled and have been omitted from the table called Airline delays 3.

a. The departure time of a flight refers to the difference, if any, between the scheduled departure and the time at which the plane rolls away from gate.
Create an XBar-S chart for DepDelay and report on the extent to which this process seems to be under control. Use a sample size of 20 flights.

b. The data table also contains a column labeled SchedDeptoWheelsOff, which is the elapsed time between scheduled departure and the moment when the wheels leave the runway. Create an XBar-S chart for this variable (n = 20)
and report on the extent to which this process seems to be under control.
How does it compare to the previous chart?

c. (Challenge) Imagine that the airline would like to control departure delays with a goal of having 90% of all non-cancelled weekday flights leave the gate 20 minutes or less from the scheduled time. Run a capability analysis, and report on your findings. Hint: the column called Weekend is a dummy variable equal to 1 for Saturday and Sunday flights.