Case 1:
Modified last: October 27
HP is America West.
Another link to an airport code site:
http://www.uni-karlsruhe.de/~un9v/atm/ase.html
Questions and
answers. -last modified
October 27
Here
is an Excel workbook that illustrates how to easily select random
samples. Automatic calculation is turned off, so you have to manually
recalcuate when you want to "sample."
Data:
ASQP
data elements description (excel)
ASQP
data for July 1997 (tab delimited
text) - for flights into
and out of Boston
ASQP
data for February 1998 (tab delimited
text) - for flights into
and out of Boston
ASQP
data for February 1998
with column headings
Airport
codes - a list of the
three letter codes
http://www.airnav.com/
- details about airports; can search for codes not in the airport
codes link
http://www.fare.net/air.html
- list of airline web sites, includes IATA carrier code, e.g.,
AA
- Look at the AA (American Airlines) flights between BOS (Boston
Logan) and SJC (San Jose, California) as well as the AA flights
between SJC and BOS.
- Graph the frequency distribution of the block
times for each of the flights.
- Calculate the mean and standard deviation for each flight
number's (e.g., 128) block times.
- Do you notice anything interesting? What?
- Assume each flight is a Bernoulli trial. Assume that success
could be defined in two different ways: 1) in which sucess is
defined to be "actual arrival time within 15 minutes of scheduled
arrival time" and 2) in which success is defined to be "actual
arrival time less than or equal to scheduled arrival time." Assume
that for passengers, p (the probability of success) is the primary
measure of system performance. Analyze system performance across
different city-pairs (origin and destination for a given
flight), different airlines and different
seasons.
- Assume that the ASQP data includes all flights into and out of
BOS (it doesn't). Estimate the maximum arrival acceptance rate and
maximum departure rate at BOS. Analyze the operation of BOS
relative to these maximum rates.
- Are the mean block times between city-pairs the same
independent of direction? Are the mean block times significantly
different in different months?
- Analyze delays (e.g., departure, arrival, total) for flights
into and out of Boston. A few suggestions (don't limit yourself to
just these):
- Develop a delay model. Estimate various parameters
related to your model. Consider factors such as city-pairs,
airlines, congestion, season, time of day, congestion, etc. See
if there are significant differences in delay parameters across
these factors.
- Analyze the relationship between tardiness (define tardy
as: a flight is tardy if it arrives after the scheduled time)
and scheduled block times. Analyze the relationship with other
variables. Consider factors such as city-pairs, airlines,
congestion, season, time of day, congestion, etc.