APP MTH 4052 - Applied Mathematics Topic F - Honours
North Terrace Campus - Semester 2 - 2021
General Course Information
Course Code APP MTH 4052 Course Applied Mathematics Topic F - Honours Coordinating Unit Mathematical Sciences Term Semester 2 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 2.5 hours per week Available for Study Abroad and Exchange Y Restrictions Honours students only 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: Professor Matthew RoughanThis is the same course as APP MTH 7088 - Applied Mathematics Topic F
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning Outcomes
In 2021 the topic of this course will be Complex network modelling and inference.
This course will study graphs and networks, and their generalisations as applied to modelling of complex systems of interacting components or actors. We'll go somewhat beyond standard graph theory in that we will consider how quantities associated with links affect real network problems. In particular, we will consider how to statistically infer properties of networks from realistically obtainable metrics when the networks are large, and we cannot query the network directly, but must use indirect measurement strategies. Applications range from management of computer networks to analysis of social phenomenon, such as memes that "go viral".
1. Modelling: model a problem
- Take a problem stated in words, and convert it into mathematical form
- Consider assumptions and approximations
- Deal with incomplete information/ideas by asking questions, and investigation
2. Analysis: analyse the problem using diverse tools
- Analysis (mathematical solution of problems)
- Statistics (incorporating data)
3. Critically examine results:
- Sanity checking
- Close the loop between modelling->analysis->output
- Sensitivity analysis
4. Communicate results
- Mathematical exposition skills
Pre-requisites and assumed knowledge:
Mathematics up to second year level will be required, including
- Probability and Statistics II,
- Scientific Computing or equivalent.
In particular, this project will require some programming (Matlab or another language is acceptable).
Some knowledge of graph theory would be useful.
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) Deep discipline knowledge
- informed and infused by cutting edge research, scaffolded throughout their program of studies
- acquired from personal interaction with research active educators, from year 1
- accredited or validated against national or international standards (for relevant programs)
all Critical thinking and problem solving
- steeped in research methods and rigor
- based on empirical evidence and the scientific approach to knowledge development
- demonstrated through appropriate and relevant assessment
all Teamwork and communication skills
- developed from, with, and via the SGDE
- honed through assessment and practice throughout the program of studies
- encouraged and valued in all aspects of learning
all Self-awareness and emotional intelligence
- a capacity for self-reflection and a willingness to engage in self-appraisal
- open to objective and constructive feedback from supervisors and peers
- able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
Required ResourcesAll required materials will be provided.
Recommended Resources"Networks: An Introduction", M.E.J. Newman, Oxford Uni Press, 2010.
Online LearningThis course uses MyUni exclusively for providing electronic resources, such as lecture notes, assignment papers, and sample solutions. Students should make appropriate use of these resources.
Learning & Teaching Activities
Learning & Teaching ModesThis course relies on combined lecture and tutorial classes as the primary learning mechanism for the material. A sequence of written and/or online assignments provides assessment opportunities for students to gauge their progress and understanding.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
Activity Quantity Workload Hours Lectures 30 90 Tutorials 6 18 Assignments 4 24 Project 1 24 Total 156
Learning Activities SummaryLecture Outline
- graph theory basics
- graph metrics
- random graph models
- algorithms on graphs
- Advanced Topics
- graph generalisations: hyper-graphs and meta-graphs
- graph algebras
- sampling from networks
- inference on graphs: network tomography
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 Ongoing assessment 50% all Exam 50% all
For details of on-going assessment refer to my-uni course.
Assessment Related RequirementsAn aggregate score of at least 50% is required to pass the course.
Assessment item Distributed Due date Weighting Assignment 1 Week 2 Week 4 5% Assignment 2 Week 4 Week 6 5% Assignment 3 Week 7 Week 9 5% Assignment 4 Week 9 Week 11 5% Project Week 6 Week 13 10%
SubmissionHomework assignments must either be given to the lecturer in person or left in the box outside the lecturer's office by the given due time. Failure to meet the deadline without reasonable and verifiable excuse may result in a significant penalty for that assignment. The last day on which a miniproject may be submitted is the last teaching day of the semester.
Grades for your performance in this course will be awarded in accordance with the following scheme:
M11 (Honours Mark Scheme) Grade Grade reflects following criteria for allocation of grade Reported on Official Transcript Fail A mark between 1-49 F Third Class A mark between 50-59 3 Second Class Div B A mark between 60-69 2B Second Class Div A A mark between 70-79 2A First Class A mark between 80-100 1 Result Pending An interim result RP Continuing Continuing CN
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.
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