| Effective Term: | 2026/05 |
| Institute / School : | Institute of Innovation, Science & Sustainability |
| Unit Title: | Applied Mathematics 2 |
| Unit ID: | GPMAT2100 |
| Credit Points: | 15.00 |
| Prerequisite(s): | Nil |
| Co-requisite(s): | Nil |
| Exclusion(s): | Nil |
| ASCED: | 010101 |
| Other Change: | |
| Brief description of the Unit |
This unit aims to offer students from diverse backgrounds an introduction to the use of mathematical methods applicable to business, industry, engineering and science. The unit introduces students to the concepts and techniques of linear algebra and linear programming which have applications in various fields. In addition, an introduction to statistics with applications is considered. The unit will be particularly valuable to STEM students, prospective senior secondary school mathematics teachers, and any student interested in improving their understanding of these commonly encountered concepts and applications of mathematics. This unit will also incorporate additional learning hours to support the development of students’ academic and study skills. |
| Grade Scheme: | Graded (HD, D, C, P, MF, F, XF) |
| Work Experience Indicator: |
| No work experience |
| Placement Component: | |
| Supplementary Assessment:Yes |
| Where supplementary assessment is available a student must have failed overall in the Unit but gained a final mark of 45 per cent or above, has completed all major assessment tasks (including all sub-components where a task has multiple parts) as specified in the Unit Description and is not eligible for any other form of supplementary assessment |
| Course Level: |
| Level of Unit in Course | AQF Level(s) of Course | | 5 | 6 | 7 | 8 | 9 | 10 | | Introductory | | | | | | | | Intermediate |  | | | | | | | Advanced | | | | | | |
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| Learning Outcomes: |
| Knowledge: |
| K1. | Recognise the basic techniques used for solving problems in linear algebra. |
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| K2. | Explain and classify the fundamental structure of vectors, matrices and matrix arithmetic. |
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| K3. | Express real world problems into mathematical models using linear equations and inequalities to represent objecitve function and constraints. |
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| K4. | Recognise basic statistical concepts used to solve problems in STEM. |
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| Skills: |
| S1. | Perform operations on vectors and matrices. |
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| S2. | Solve systems of linear equations. |
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| S3. | Solve constrained optimisation problems using linear programming. |
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| S4. | Utilise appropriate software to assist in the solution and investigation of problems. |
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| S5. | Develop the appropriate English language and academic skills to successfully study at an undergraduate level |
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| Application of knowledge and skills: |
| A1. | Apply statistical techniques to investigate problems in STEM. |
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| A2. | Formulate basic problems in STEM as mathematical problems using concepts from linear algebra and linear programming. |
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| Unit Content: |
Topics may include:
1. Vector spaces, inner products, linear independence, basis, dimension and rank of matrices;
2. Matrix representations and solving of systems of linear equations.
3. Operations research (Linear programming and scheduling techniques).
4. Statistics basics and applications |
| Graduate Attributes: |
| | Learning Outcomes Assessed | Assessment Tasks | Assessment Type | Weighting | | 1. | K1, K4, S1, S2, S3, S4, S5 | Weekly learning activities | Tutorials/labs | 0-30% | | 2. | K1, K2, K3, K4, S1, S2, S3, S4, S5, A1, A2 | A range of tasks and problems are explored to support the understanding of the content and the development of skills and knowledge throughout the unit. | Assignment(s) | 30% - 50% | | 3. | K3, S2, S3, S4, S5, A1, A2 | Students work collaboratively to explore a range of mathematical tasks and problems, deepening their understanding of key concepts and enhancing their mathematical communication skills. The learning process culminates in a group presentation. | Presentation(s) | 20% - 40% | | 4. | K1, K2, K3, K4, S1, S2, S3, S4, A1 | Students will provide theoretical answers and practical solutions to a range of questions and problem types drawn from theory and examples used during this unit. | Test(s) | 20-30% |
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