Overview

In this unit students will extend their quantitative and qualitative analytical capabilities and learn to apply them in a structured and methodological approach in order to offer critical insight to aviation industry problems. Using industry standard tools students will apply inferential statistical methods and research design principles to deliver objective and reliable aviation business insight.

Requisites

Teaching Periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Semester 1
Location
Hawthorn
Start and end dates
26-February-2024
26-May-2024
Last self-enrolment date
10-March-2024
Census date
31-March-2024
Last withdraw without fail date
12-April-2024
Results released date
02-July-2024

Learning outcomes

Students who successfully complete this unit will be able to:

  • Apply inferential statistical techniques to aviation data to generate sophisticated understanding of practical business problems
  • Confidently utilise industry standard advanced analytical tools
  • Interface multiple tools, techniques, and data sources to create an analysis pipeline which addresses a specific industry problem
  • Devise an appropriate research framework to address quantitative, qualitative or mixed applied aviation challenges
  • Describe the challenges and opportunities related to emerging issues in data science and analytics in the aviation industry

Teaching methods

Hawthorn

Type Hours per week Number of weeks Total (number of hours)
On-Campus
Lecture
2.00  12 weeks  24
On-Campus 
Tutorial Labs
1.00  12 weeks  12
Unspecified Activities 
Independent Learning
9.50  12 weeks  114
TOTAL     150

Assessment

Type Task Weighting ULO's
AssignmentIndividual 30 - 40% 1,2 
AssignmentIndividual/Group 30 - 40% 3,4 
PresentationIndividual/Group 30 - 40% 1,4,5 

Content

Emerging Issues in Aviation Data Analytics
- Big Data
- Forecasting
- Machine learning

Data Analysis
- Different technologies used for data analysis – i.e. SPSS, PowerBI, Tableau, Palisade

Decision Tools
- Analysing large complex datasets using various mathematical techniques and models
- Inferential statistics and multivariate analysis
- Formulating a business problem as a decision model
- Applying decision analytic methods to obtain efficient solutions to a variety of complex business problems

Data Visualisation
- Dashboard design for Managers
- Different methods for presenting qualitative and quantitative data
- Selecting appropriate visual representations to communicate data

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.