| Semester 2, 2020 Online | |
| Short Description: | Maths/Stats Comple'y Studies B |
| Units : | 1 |
| Faculty or Section : | Faculty of Health, Engineering and Sciences |
| School or Department : | School of Sciences |
| Student contribution band : | Band 2 |
| ASCED code : | 010999 - Biological Sciences not elsewh |
| Grading basis : | Graded |
Staffing
Examiner:
Other requisites
Enrolment in this course is only available to students in Honours and some Postgraduate programs and such enrolment requires a supervisor and the permission of the examiner and the appropriate Program Coordinator.
Depending on the topic chosen, some students may need to have successfully completed prerequisite courses.
Rationale
This course provides flexibility in honours and postgraduate programs to cater for the widely varying interests and chosen specialisations of students. Mathematicians need to be proficient in a wide range of mathematical concepts and techniques. Many of these are either only touched on or omitted from undergraduate programs. An opportunity to broaden the students' knowledge-base with more advanced concepts and techniques is provided in this course.
Synopsis
This course provides the opportunity for a student to pursue an area of study that will complement the other studies in the student's program. Typically, the course will consist of specialised investigations extending knowledge and skills in one of the areas listed in the Topics section below, or another Topic where appropriate and where a supervisor is available.
Objectives
On successful completion of this course students will be able to:
- demonstrate advanced knowledge and skills in the complementary study area.
Topics
| Description | Weighting(%) | |
|---|---|---|
| 1. |
Students should nominate the topic they wish to study; and then email the Course Examiner to enquire whether the topic and a suitable supervisor will be available in their semester of study, and for formal approval to enrol. One of the following topics can be chosen. The content of the course may vary from student to student. The weighting of the sub-topics within this course depends on the topic chosen and will be discussed with the supervisor. Modelling of Physical Systems: This course introduces extends upon concepts introduced in Mathematical Modelling and Dynamical Systems MAT3103. Topics may include Study of Particular Dynamical Systems in Application to Engineering or other fields; Calculus of Variations. Qualitative Methods of Solutions of Differential Equations; Study of Phase Plane Analysis; Exact Methods in Nonlinear Wave Theory. (This is not compatible with MAT3103) Financial Mathematics This course introduces and extends upon the methods and theory introduced in MAT3104 Mathematical Modelling in Financial Economics. Topics include financial and commercial applications of mathematics where Stochastic Differential Equations (SDEs) are of fundamental importance. SDEs also apply in many other areas in science and engineering and have many features that distinguish them from other mathematical models. (This is not compatible with MAT3104). Mathematics Education: This course is designed for students interested in expanding their knowledge in one or more areas of mathematics education. Topics could include: the role of language in learning and understanding mathematics; issues in adult, academic and everyday numeracy; fundamental constructs in mathematics education; history and philosophy of mathematics. Predictive Modelling with Random Forest, Multiple Regressions and Optimisation of Neural Networks: A number of analytical techniques related to ANN, MLR and RF models are introduced; and the data analyses and modelling is performed. The modelling in the course will focus on optimisation of an ANN and evaluation of the optimised model with MLR and RF models. RF models will be optimised by deducing the optimal combination of training algorithm, hidden transfer/output equations and data division between training, validation and testing subsets. Some programming in MATLAB, R or Python is assumed. Operations Research: This topic introduces and extends upon the methods and theory in Operations Research 1 MAT2200. It focuses on the model development, analytical techniques and the background mathematics necessary for the solution and post-optimal analysis of linear programming, integer programming, transportation, assignment, graph, network, and critical path problems. (This is not compatible with MAT2200.) |
100.00 |
Text and materials required to be purchased or accessed
ALL textbooks and materials available to be purchased can be sourced from (unless otherwise stated). (https://omnia.usq.edu.au/textbooks/?year=2020&sem=02&subject1=MAT8190)
Please for alternative purchase options from USQ Bookshop. (https://omnia.usq.edu.au/info/contact/)
Reference materials
Student workload expectations
| Activity | Hours |
|---|---|
| Assessments | 20.00 |
| Private Study | 90.00 |
| Project Work | 40.00 |
| Supervisor Consultation | 15.00 |
Assessment details
| Description | Marks out of | Wtg (%) | Due Date | Notes |
|---|---|---|---|---|
| ASSIGNMENT 1 | 40 | 40 | 22 Oct 2020 | |
| ASSIGNMENT 2 (PROJECT) | 60 | 60 | 22 Oct 2020 |
Important assessment information
-
Attendance requirements:
It is the student's responsibility to study all material provided to them or required to be accessed by them to maximise their chance of meeting the objectives of the course and to be informed of course-related activities and administration. -
Requirements for students to complete each assessment item satisfactorily:
Requirements for students to complete each assessment item satisfactorily: To satisfactorily complete an individual assessment item a student must achieve at least 50% of the marks or a grade of at least C. -
Penalties for late submission of required work:
Students should refer to the Assessment Procedure (point 4.2.4) -
Requirements for student to be awarded a passing grade in the course:
To be assured of receiving a passing grade a student must achieve at least 50% of the total weighted marks available for the course. -
Method used to combine assessment results to attain final grade:
The final grades for students will be assigned on the basis of the weighted aggregate of the marks obtained for each of the summative assessment items in the course. -
Examination information:
There is no examination in this course. -
Examination period when Deferred/Supplementary examinations will be held:
As there are no examinations in this course, there will be no deferred or supplementary examinations. -
University Student Policies:
Students should read the USQ policies: Definitions, Assessment and Student Academic Misconduct to avoid actions which might contravene University policies and practices. These policies can be found at . In particular, Students must familiarise themselves with the USQ Assessment Procedures (.