The information will not be changed unless absolutely necessary and any change will be clearly indicated by an approved correction included in the profile.
Unit Profile Correction added on 18-02-25
Learning Outcome 1 is updated to "Apply the International Civil Aviation Organisation (ICAO) Statistics Programme and/or other government-published aviation data set to an air transport scenario".
Current Learning Outcome 1 is for students to: "Apply the International Civil Aviation Organisation (ICAO) Statistics Programme to an air transport scenario". However, ICAO is a very expensive database that is not unnecessary when there are other excellent government-published data sources for use in this unit. Therefore, for the delivery in T1, this learning outcome is updated to "Apply the International Civil Aviation Organisation (ICAO) Statistics Programme and/or other government-published aviation data set to an air transport scenario" to make the unit more accessible for all students.
Overview
Aviation Data Analysis will introduce statistical analysis techniques for aviation service providers (Airports, Airlines and Air Traffic Control Management units), based on the International Civil Aviation Organisation (ICAO) program and recommendation on air transport. You will learn about applications of Statistical Analysis and Forecasting Techniques in management practice and, you will apply these techniques in quantitative practical workshops designed to improve your analytical skills in an aviation context.
Details
Pre-requisites or Co-requisites
Students must meet the following prerequisites: 1. Students must complete both of the following units:AVAT11008 Introduction to Aviation ManagementAVAT12020 Airline Resource Management 2. Students must also complete one of the following units: AVAT11013 Introduction to AviationAVAT11002 Basic Aeronautical Knowledge
Important note: Students enrolled in a subsequent unit who failed their pre-requisite unit, should drop the subsequent unit before the census date or within 10 working days of Fail grade notification. Students who do not drop the unit in this timeframe cannot later drop the unit without academic and financial liability. See details in the Assessment Policy and Procedure (Higher Education Coursework).
Offerings For Term 1 - 2025
Attendance Requirements
All on-campus students are expected to attend scheduled classes - in some units, these classes are identified as a mandatory (pass/fail) component and attendance is compulsory. International students, on a student visa, must maintain a full time study load and meet both attendance and academic progress requirements in each study period (satisfactory attendance for International students is defined as maintaining at least an 80% attendance record).
Recommended Student Time Commitment
Each 6-credit Undergraduate unit at CQUniversity requires an overall time commitment of an average of 12.5 hours of study per week, making a total of 150 hours for the unit.
Class Timetable
Assessment Overview
Assessment Grading
This is a graded unit: your overall grade will be calculated from the marks or grades for each assessment task, based on the relative weightings shown in the table above. You must obtain an overall mark for the unit of at least 50%, or an overall grade of 'pass' in order to pass the unit. If any 'pass/fail' tasks are shown in the table above they must also be completed successfully ('pass' grade). You must also meet any minimum mark requirements specified for a particular assessment task, as detailed in the 'assessment task' section (note that in some instances, the minimum mark for a task may be greater than 50%). Consult the University's Grades and Results Policy for more details of interim results and final grades.
All University policies are available on the CQUniversity Policy site.
You may wish to view these policies:
- Grades and Results Policy
- Assessment Policy and Procedure (Higher Education Coursework)
- Review of Grade Procedure
- Student Academic Integrity Policy and Procedure
- Monitoring Academic Progress (MAP) Policy and Procedure - Domestic Students
- Monitoring Academic Progress (MAP) Policy and Procedure - International Students
- Student Refund and Credit Balance Policy and Procedure
- Student Feedback - Compliments and Complaints Policy and Procedure
- Information and Communications Technology Acceptable Use Policy and Procedure
This list is not an exhaustive list of all University policies. The full list of University policies are available on the CQUniversity Policy site.
Feedback, Recommendations and Responses
Every unit is reviewed for enhancement each year. At the most recent review, the following staff and student feedback items were identified and recommendations were made.
Feedback from UC Reflections
Feedback Item Seeking mid-term student feedback
The mid-term in-class student survey should continue to facilitate timely improvements to the student learning experience.
- Apply the International Civil Aviation Organisation (ICAO) Statistics Programme to an air transport scenario
- Forecast aviation traffic through use of descriptive statistics principles including linear and multiple regression models
- Discuss principles governing statistical activities and the methods of calculating airport performance measures
- Demonstrate advanced management skills including problem-solving and written communication.
NA
Alignment of Assessment Tasks to Learning Outcomes
| Assessment Tasks | Learning Outcomes | |||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| 1 - Online Quiz(zes) - 30% | ||||
| 2 - Case Study - 30% | ||||
| 3 - Group Work - 40% | ||||
Alignment of Graduate Attributes to Learning Outcomes
| Graduate Attributes | Learning Outcomes | |||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| 1 - Communication | ||||
| 2 - Problem Solving | ||||
| 3 - Critical Thinking | ||||
| 4 - Information Literacy | ||||
| 5 - Team Work | ||||
| 6 - Information Technology Competence | ||||
| 7 - Cross Cultural Competence | ||||
| 8 - Ethical practice | ||||
| 9 - Social Innovation | ||||
| 10 - Aboriginal and Torres Strait Islander Cultures | ||||
Textbooks
An Introduction to Mathematical Statistics
Edition: 5
Authors: Richard J. Larsen, Morris L. Marx
Pearson
ISBN: 0321693949
Business statistics : a decision-making approach
Edition: 10th (2014)
Authors: Groebner, David F., author. | Shannon, Patrick W., author. | Fry, Phillip C.
Pearson
ISBN: 978-0134496498
Additional Textbook Information
www.python.org - Students need to install Python3 in their laptop/desktop.
IT Resources
- CQUniversity Student Email
- Internet
- Unit Website (Moodle)
- python 3.10 or higher
- APA Style Writing - https://apastyle.apa.org/products/publication-manual-7th-edition
- Markdown Guide - https://www.markdownguide.org/
- Latex Guide - https://www.overleaf.com/learn/latex/Learn_LaTeX_in_30_minutes
All submissions for this unit must use the referencing style: American Psychological Association 7th Edition (APA 7th edition)
For further information, see the Assessment Tasks.
q.zhang@cqu.edu.au
Module/Topic
Lecture: Introduction to Data Collections and ICAO Statistics:
- Overview of course objectives and structure
- Introduction to ICAO Statistics Program and data collections
Tutorial: Setting up Python environment, exploring sample datasets (CSV files), basic operations in Python (importing data, checking data structure).
Chapter
Business statistics: CH1
Events and Submissions/Topic
Module/Topic
Lecture: Descriptive Statistics Principles
Tutorial: Calculating and interpreting descriptive statistics for aviation data using Python libraries like Pandas
Chapter
Business statistics: CH3
Events and Submissions/Topic
Module/Topic
Lecture: Data Visualization and Exploratory Data Analysis
Tutorial: Analyzing airline traffic data using Python libraries like Pandas. Visualizing ICAO data using Python libraries like Matplotlib and Seaborn
Chapter
Business statistics: CH2
Events and Submissions/Topic
Homework and Code Assignment 1.1 Due
Module/Topic
Lecture: Simple Linear Regression and Forecasting
Tutorial: Fitting a simple linear regression model, and forecasting
Chapter
Mathematics statistics: CH11.1-11.2
Events and Submissions/Topic
Module/Topic
Lecture: Multiple Regression and Model Diagnostics
Tutorial: Building and diagnosing a multiple regression model for aviation traffic forecasting
Chapter
Mathematics statistics: CH11.3
Events and Submissions/Topic
Module/Topic
Term Break
Chapter
Events and Submissions/Topic
Module/Topic
Lecture: Basic Probability
Tutorial: Calculating probabilities for aviation events
Chapter
Business statistics: CH4
Events and Submissions/Topic
Homework and Code Assignment 1.2 Due
Module/Topic
Lecture: Important Discrete Probability Distributions
Tutorial: Simulating aviation events using discrete probability distributions
Chapter
Business statistics: CH5
Events and Submissions/Topic
Module/Topic
Lecture: The Normal Distribution and Other Continuous Distributions
Tutorial: Analyzing aviation data using continuous probability distributions
Chapter
Business statistics: CH6
Events and Submissions/Topic
Module/Topic
Lecture: Sampling Distributions and Central Limit Theorem
Tutorial: Understanding sampling distributions and the Central Limit Theorem in aviation data
Chapter
Business statistics: CH7
Events and Submissions/Topic
Module/Topic
Lecture: Hypothesis Testing and Confidence Intervals
Tutorial: Conducting hypothesis tests on datasets
Chapter
Mathematics statistics: CH6.1-6.5
Business statistics: CH8
Events and Submissions/Topic
Homework and Code Assignment 1.3 Due
Module/Topic
Lecture: Statistical Quality Checks and Predictive Modelling
Tutorial: Implementing quality checks on aviation data, training predictive models
Chapter
Mathematics statistics: CH6.1-6.5
Business statistics: CH8
Events and Submissions/Topic
Review the topics
Module/Topic
Final Project Presentation and Evaluation
Chapter
Events and Submissions/Topic
Module/Topic
Final Test
Chapter
Events and Submissions/Topic
Due: Exam Week Friday (13 June 2025) 5:00 pm AEST
Final test Due: Review/Exam Week Friday (13 June 2025) 5:00 pm AEST
Module/Topic
None
Chapter
Events and Submissions/Topic
Communication
Please use AVAT13023 as the first word in the subject line for emails. Typically, I will be able to answer emails within 2 business days, unless I am away for an extended period of time. In your emails, always end the email with your name and CQU email address.
Writing Style
Students are recommended to purchase the Manual of Publication by the American Psychological Association (APA) (7th Ed.). It is the major reference source for style or format questions in aviation program. The format of references, citations, quotation, and headings should be identical to APA requirements. Be sure to read and understand the plagiarism sections.
Use of Generative AI
The use of generative AI (e.g. ChatGPT) to create original text is strictly prohibited in this unit. Students may use AI-based support tools to enhance the quality of existing text or improve spelling, grammar, etc. To ensure appropriate use of generative AI tools and avoid accidental misuse, students should liaise with the CQU Academic Learning Centre (ALC) at https://www.cqu.edu.au/study/experience/support/academic-learning-centres.
1 Online Quiz(zes)
There are three quizzes (which include coding assignments) scheduled throughout this unit:
- Quiz 1: Due before Week 4 Lecture (Tuesday 9:00 AM), covering basic data concepts and fundamental statistical principles.
Quiz 2: Due before Week 7 Lecture (Tuesday 9:00 AM), focusing on regression models and their applications.
Quiz 3: Due before Week 11 Lecture (Tuesday 9:00 AM), addressing probability, distributions, and hypothesis testing.
Each quiz will be made available on Moodle at least two weeks prior to its due date. You must submit your completed assignments with required results and outcomes before the specified Week Lecture time via the relevant portal in Moodle. Late submissions may not be accepted.
3
TBA
TBA
- Purpose: The quizzes serve as formative assessments to ensure you comprehend core topics and can apply them in practical scenarios.
- Format:
- Each quiz may include short-answer (calculations or derivations), and coding components to evaluate your data analysis skills.
You will access all quizzes instructions through Moodle under the “Assessments” section.
- Each quiz may include short-answer (calculations or derivations), and coding components to evaluate your data analysis skills.
- Weighting:
- Each quiz is worth 10% of your final grade, totaling 30% across the three quizzes.
- Quizzes must be submitted by the posted deadlines; no alternative submission methods (e.g., email) are permitted.
- Apply the International Civil Aviation Organisation (ICAO) Statistics Programme to an air transport scenario
- Discuss principles governing statistical activities and the methods of calculating airport performance measures
2 Case Study
You are required to research and analyze an aviation-related datasets using the statistical and data analysis methods learned in this unit. This assessment can be completed individually, or if the class exceeds 10 students, you may collaborate in pairs (maximum of two people).
- Presentation
- A 5–10-minute presentation of your case study delivered to the class either in person or via Zoom during Week 12.
- You must upload your presentation to Moodle by the deadline specified in the unit profile.
- Presentations exceeding the 10-minute limit by more than one minute will result in a 10% grade deduction.
- Students are encouraged to be creative with the presentation style and formatting, however students should ensure that the presentation is easy to understand and is not distracting from the content.
-
Written Report
-
- Outline: Submit a brief outline in Week 6, stating your initial research idea, data sources, and a proposed project timeline.
- Full Report: Submit a comprehensive report by Week 12 describing your findings and analysis.
- Requirements:
- Length: 5–10 pages (excluding references, figures, and tables).
- Format: Follow APA style guidelines, including but not limited to 1-inch margins, 12-point Times New Roman font, and double spacing.
- Visuals: Include relevant figures and tables; if numerous, place them in an appendix.
- Submission: Upload the final report to Moodle by the specified deadline. You may use either Overleaf (Recommended) or Word, following the provided templates.
Week 12 Tuesday (3 June 2025) 9:00 am AEST
TBA
TBA
You will be evaluated on both your presentation and the written report, with a total of 30 points available:
- Overall Objective: Demonstrate accurate application of statistical and data analysis techniques to aviation data,
- Descriptive statistics (e.g., ICAO data)
- Data visualization and exploratory data analysis
- Regression analysis for forecasting, or clustering techniques
- Hypothesis testing or time series analysis
Presentation (10 Points)
- Content Understanding (5 Points): Clear and concise background, analysis, and conclusion of your research.
- Delivery and Communication (4 Points): Presentation is well-organized and engaging.
- Professionalism (1 Points): Adherence to presentation guidelines and time management.
Written Report (20 Points)
- Outline and Proposed Timeline (4 Points): Submission of report outline with a clear plan in Week 6.
- Research Motivation (5 Points): Explanation of the importance and relevance of the chosen case.
- Data Analysis and Findings (8 Points): Appropriate use of statistical methods or data science tools and alignment with the overall project objectives.
- Clarity and Cohesion (3 Points): Logical flow of information and coherent argumentation.
- Writing Quality (2 Points): Grammar, style, and readability.
- Formatting and Presentation (1 Point): Compliance with APA style and template usage.
- References and Citations (1 Point): Properly cited sources.
- Submission Instructions (1 Point): Correct and timely submission following all guidelines.
- Apply the International Civil Aviation Organisation (ICAO) Statistics Programme to an air transport scenario
- Forecast aviation traffic through use of descriptive statistics principles including linear and multiple regression models
- Demonstrate advanced management skills including problem-solving and written communication.
3 Group Work
The final test will be held during the exam week and will cover the material from Weeks 1–11.
Duration and Format:
- You have 3 hours to complete the test once started, with only one attempt permitted.
- The test will open on Monday morning of the exam week and must be submitted by Friday at 5:00 PM (AEST) through Moodle.
Instructions:
- Accessing the Test: Available via the designated Moodle portal on Monday morning of exam week.
- Submission Deadline: No extensions—late submissions will not be accepted.
- Technical Requirements: Ensure a stable internet connection.
- One-Time Entry: Once you begin, you must complete the entire test within 3 hours. There is no opportunity to submit the answers after the allotted time, and submission via email is not acceptable.
- Permitted Resources: Textbooks, personal notes, a calculator, a computer (with a suitable Python environment), and a prepared “cheat sheet” for quick reference. Considering time constraints, it is recommended to prepare a cheat sheet in advance for quick reference.
- File Upload:
- Answers must be uploaded as a PDF, along with any corresponding Python files or Jupyter notebooks.
- You may scan or photograph handwritten solutions, provided the images are clear and legible.
- Latex-generated PDFs are recommended for clarity.
Below is a list of recommended camera scanning apps suitable for this purpose. Be sure to download your chosen app before the exam to ensure a smooth scanning process if you do not have devices such scanner or digital input pad.
- Adobe Scan (DC) https://adobescan.app.link/d/1n1NntFHTkb
- Microsoft Lens https://apps.apple.com/au/app/microsoft-lens-pdf-scanner/id975925059
- SwiftScan https://swiftscan.app/en/index.html
- CamScanner https://www.camscanner.com/
- ClearScan https://clearscanapp.com/
Review/Exam Week Friday (13 June 2025) 5:00 pm AEST
TBA
TBA
The Final Test is designed to evaluate your comprehensive understanding and application of the course material from Weeks 1–11. The assessment comprises three distinct sections: Multiple-Choice Questions, Short-Answer Questions, and Python Coding Tasks. Below are the general evaluation standards.
- Comprehensive Coverage: The test will encompass all major topics discussed from Weeks 1–11. Ensure thorough revision of lectures, readings, and assignments.
- Application of Knowledge: Ability to not only recall information but also apply concepts to novel scenarios, particularly in coding tasks.
- Time Management: Efficient allocation of time across different sections to complete all tasks within the 3-hour limit.
- Submission Compliance: Adherence to file format requirements and timely submission as per the guidelines.
- Forecast aviation traffic through use of descriptive statistics principles including linear and multiple regression models
- Discuss principles governing statistical activities and the methods of calculating airport performance measures
- Demonstrate advanced management skills including problem-solving and written communication.
As a CQUniversity student you are expected to act honestly in all aspects of your academic work.
Any assessable work undertaken or submitted for review or assessment must be your own work. Assessable work is any type of work you do to meet the assessment requirements in the unit, including draft work submitted for review and feedback and final work to be assessed.
When you use the ideas, words or data of others in your assessment, you must thoroughly and clearly acknowledge the source of this information by using the correct referencing style for your unit. Using others’ work without proper acknowledgement may be considered a form of intellectual dishonesty.
Participating honestly, respectfully, responsibly, and fairly in your university study ensures the CQUniversity qualification you earn will be valued as a true indication of your individual academic achievement and will continue to receive the respect and recognition it deserves.
As a student, you are responsible for reading and following CQUniversity’s policies, including the Student Academic Integrity Policy and Procedure. This policy sets out CQUniversity’s expectations of you to act with integrity, examples of academic integrity breaches to avoid, the processes used to address alleged breaches of academic integrity, and potential penalties.
What is a breach of academic integrity?
A breach of academic integrity includes but is not limited to plagiarism, self-plagiarism, collusion, cheating, contract cheating, and academic misconduct. The Student Academic Integrity Policy and Procedure defines what these terms mean and gives examples.
Why is academic integrity important?
A breach of academic integrity may result in one or more penalties, including suspension or even expulsion from the University. It can also have negative implications for student visas and future enrolment at CQUniversity or elsewhere. Students who engage in contract cheating also risk being blackmailed by contract cheating services.
Where can I get assistance?
For academic advice and guidance, the Academic Learning Centre (ALC) can support you in becoming confident in completing assessments with integrity and of high standard.
What can you do to act with integrity?
