You are provided with a dataset downloaded from data.gov.au. The dataset is available on Moodle and consists of
monthly number of flights per route for the last 5 years. The variables include:
– Route: the flight route
– Departing_Port: Airport of departure
– Arriving_Port: Airport of arrival
– Airline: the airline
– Year: the year the flights took place
– Month: the month the flights took place (e.g. “Jan”, “Feb”, …)
– Month_Num: the month number the flights took place (e.g. 1 for Jan, 2 for Feb, …)
– Cancellations: the number of cancelled flights during a given month
– Departures_On_Time: the number of flights departed on time during a given month
– Arrivals_On_Time: the number of flights arrived on time during a given month
– Departures_Delayed: the number of flights departed with some delay during a given month
– Arrivals_Delayed: the number of flights arrived with some delay during a given month
You must present your findings, supported by data visualisations, in the form of a written report (approx. 750 words)
that should include:
– A summary of descriiptive statistics of relevant variables in the dataset and why you think such variables are
relevant to your analysis
– Descriiption of data aggregations that you deem necessary to conduct your analysis
– A visual data analysis (including graphs) to identify:
o TWO (2) relevant factors impacting flight delays for Qantas and its competitors
o TWO (2) relevant factors impacting flight cancellations for Qantas and its competitors
– Interpretation of your findings and actionable insights that you could derive to help Qantas improve its
performance