Course Title: Aviation Mathematics
Part A: Course Overview
Course Title: Aviation Mathematics
Credit Points: 12.00
Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
MATH2314 |
City Campus |
Undergraduate |
145H Mathematical & Geospatial Sciences |
Face-to-Face |
Sem 1 2016 |
MATH2314 |
City Campus |
Undergraduate |
171H School of Science |
Face-to-Face |
Sem 1 2017, Sem 1 2019, Sem 1 2020, Sem 1 2021, Sem 1 2024 |
Flexible Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
MATH2299 |
SHAPE, VTC |
Undergraduate |
171H School of Science |
Face-to-Face |
OFFSep2018 (VA1) |
MATH2299 |
SHAPE, VTC |
Undergraduate |
171H School of Science |
Face-to-Face |
OFFSep2022 (VA1) |
MATH2299 |
SHAPE, VTC |
Undergraduate |
171H School of Science |
Face-to-Face |
OFFSep2023 (VA1) |
Course Coordinator: Dr Nur Insani
Course Coordinator Phone: +61 3 9925
Course Coordinator Email: nur.insani@rmit.edu.au
Course Coordinator Availability: By appointment, by email
Pre-requisite Courses and Assumed Knowledge and Capabilities
None
Course Description
This course provides you with mathematical statistical skills appropriate to the aviation industry. This includes statistical techniques, specifically descriptive statistics, inferential statistics, regression and time series analysis. The course also includes fundamental problem solving skills, such as problem analysis, generalisation, cross-checking, goal modification and interpretation of solutions. All applications will involve the use of Microsoft Excel to perform any of the calculations associated with these Statistical techniques. Examples will be drawn predominantly from the Aviation Industry.
Objectives/Learning Outcomes/Capability Development
This course develops and assesses the following program learning outcomes for for:
BP070P23 / BP070HKG23 / BP070SIM23 Bachelor of Applied Science (Aviation)
BP284ASA23 Bachelor of Applied Science (Aviation) / Bachelor of Business (Management)
BP345P23 Bachelor of Aviation (Pilot Training)
2. Adapt knowledge and skills to analyse and synthesise concepts, information and data in diverse aviation contexts using digital tools and professional skills.
3. Formulate ethical and evidence-based responses that integrate critical thinking, problem solving and decision making to address the challenges faced by the current and future global aviation industry.
4. Communicate and collaborate inclusively and professionally with diverse stakeholders across aviation and associated industries.
This course develops and assesses the following program learning outcomes for for:
BP070P6 / BP070HKG / Bachelor of Applied Science (Aviation)
BP284ASADD Bachelor of Applied Science (Aviation) / Bachelor of Business (Management)
BP345 Bachelor of Aviation (Pilot Training)
Problem-solving and design
- Apply problem solving, design and decision-making methodologies to develop components, systems and/ or processes to meet specified requirements, including innovative approaches to synthesise alternative solutions, concepts and procedures, while demonstrating information skills and research methods.
Abstraction and modelling
- Apply abstraction, mathematics and discipline fundamentals to analysis, design and operation, using appropriate computer software, laboratory equipment and other devices, ensuring model applicability, accuracy and limitations.
Coordination and communication
- Communicate and coordinate proficiently by listening, speaking, reading and writing English for professional practice, working as an effective member or leader of diverse teams
On completion of this course you should be able to:
- Present and describe data using various numerical and graphical procedures.
- Utilize statistical inference about sample information to arrive at probable conclusions.
- Undertake estimation and hypothesis testing.
- Use regression and correlation analysis to reveal relationships between variables and to produce forecasts of the future values of strategic variables.
- Apply general problem solving and modelling skills including problem analysis, generalization, cross-checking, goal modification and interpretation of solutions
- Demonstrate mastery of advanced functions in Excel relevant to solving mathematical problems and communicate mathematical findings and results in an unbiased manner to a non-technical audience such as decision makers, stakeholders and the general public.
Overview of Learning Activities
- Interactive lectures where underlying theory will be presented.
- Regular computer laboratory classes that will reinforce the material covered in lectures and in your independent study.
- Assignments to practice the usage of relevant software packages.
Overview of Learning Resources
RMIT will provide you with resources and tools for learning in this course through myRMIT Studies Course.
There are services available to support your learning through the University Library. The Library provides guides on academic referencing and subject specialist help as well as a range of study support services. For further information, please visit the Library page on the RMIT University website and the myRMIT student portal.
Overview of Assessment
Assessment Tasks:
Schedule A (Melbourne offering)
Assessment Task 1: In-class summative assessment
Weighting 33%
This assessment task supports CLOs 1, 2, 3, 4
Assessment Task 2: Case-based authentic evaluation of professional (statistical) skill base
Weighting 34%
This assessment task supports CLOs 4 - 6
Assessment Task 3: In-class study-based authentic assessment
Weighting 33%
This assessment task supports CLOs 1 - 5
Schedule B (Hong Kong offering)
Assessment Task 1: Case-based summative assessment
Weighting 5%
This assessment task supports CLOs 1, 2
Assessment Task 2: Mid-semester test
Weighting 20%
This assessment task supports CLOs 1, 2, 3, 4
Assessment Task 3: Case-based authentic evaluation of professional (statistical) skill base
Weighting 25%
This assessment task supports CLOs 1-6 4 - 6
Assessment Task 4: Final exam
Weighting 50%
This assessment task supports CLOs 1-5