APP MTH 7044 - Applied Mathematics Topic C
North Terrace Campus - Semester 1 - 2015
General Course Information
Course Code APP MTH 7044 Course Applied Mathematics Topic C Coordinating Unit Applied Mathematics Term Semester 1 Level Postgraduate Coursework Location/s North Terrace Campus Units 3 Available for Study Abroad and Exchange Y Course Description Please contact the School of Mathematical Sciences for further details, or view course information on the School of Mathematical Sciences web site at http://www.maths.adelaide.edu.au
Course Coordinator: Dr Andrew Coyle
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning OutcomesIn 2014 the topic of this course will be Modelling and Simulation of Stochastic Systems.
System modelling is the process of creating a model which imitates a system, generally in order to study some aspect of its operation. Many models are created to study real world or proposed systems. Some systems involve stochastic elements, in which there are many possible outcomes from the system, for example stock market prices, weather systems, or sports results. The main focus of this course will be on the use of simulation modelling for the modelling and investigation of these types of systems, although we will also look at some basic analytic mathematical models. Both techniques provide the modeller with a rich set of tools, which may be used to model many systems of interest, for example manufacturing systems, telecommunications networks, financial systems, games, ecosystems, etc. A large part of the work for this course is to complete a group project that involves simulating a system chosen by the students. This involves the design, coding, analysis and reporting of the system being simulated. The Matlab programming language is used and the aspects of this language which are needed for the project will be taught.
1) understand the basic concepts involved in designing a stochastic system model.
2) use a simulation package or a simulation program (Matlab).
3) present reults from a simulation, in both verbal and written formats.
4) work as part of a team through an extended project.
5) follow a system modelling and simulation exercise from conception through to completion.
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s) Knowledge and understanding of the content and techniques of a chosen discipline at advanced levels that are internationally recognised. 1,2,3,4,5 The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner. 1,5 An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems. 5 Skills of a high order in interpersonal understanding, teamwork and communication. 3,4 A proficiency in the appropriate use of contemporary technologies. 1,2,5 A commitment to continuous learning and the capacity to maintain intellectual curiosity throughout life. 1,5
- Simulation, Sheldon Ross (Academic Press, 2006)
- Simulation Modelling and Analysis, Averill M. Law and W. David Kelton (McGraw Hill, 2000)
- Simulation of Manufacturing Systems, A. Carrie (John Wiley & Sons, 1992)
Online LearningThis course uses MyUni exclusively for providing electronic resources, such as assignments and handouts, and for making course announcements. It is recommended that students make appropriate use of these resources. Link to MyUni login page: https://myuni.adelaide.edu.au/webapps/login/
Learning & Teaching Activities
Learning & Teaching ModesThis course relies on lectures and computer sessions as the primary delivery mechanism for the material. A software project is a major part of this course. Computer sessions will be provided to assist in the planning and work for these projects. A couple of written assignments will help students to gauge their progress and understanding of the course.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
Activity Quantity Workload Hours Lectures and Practicals 30 90 Project 1 60 Assignments 2 8 Total 158
Learning Activities SummaryLecture and Computer Practicals Outline
Week 1 Introduction to course and Matlab Week 2 Hand Simulation Week 3 Basic Simulation Techniques Week 4 Basic Probability Theory Week 5 Common Distributions Week 6 Real Data and Distributions Week 7 Project Review Week 8 Random Number Generation Week 9 Random Variate Generation Week 10 Elementary Analysis of Simulation Output Week 11 Project Presentations Week 12 Summary and Revision
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Component Weighting Objective Assessed Exam 70% all Project 30% all Assignments None
Assessment DetailThere will be a single group project worth 30% of the total mark. The remaining 70% will come from the exam. The details of this project will be given out at the first lecture. Every week there will be a computer session in which help with with the project will be available. The lecturer will review the project in Week 7 to ensure that the it is on a reasonable track. Compulsory group project presentations will take place in Week 11. The projects must be submitted electronically before the end of Week 12.
There will be two exercises given out at Week 4 and Week 8. These are not compulsory but are exercises similar to the questions that will appear in the exam. Answers may be submitted the following week (Weeks 5 and 9) and will then be returned the next week (Weeks 6 and 10).
SubmissionAssignments must be handed in person to the lecturer if they are to be marked.
The project must be delivered electronically to the lecturer before the end of Week 12. The submission must include both the report and the corresponding Matlab code. Late submission of the project will invoke a penalty.
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending
Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through Access Adelaide.
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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