APP MTH 4052 - Applied Mathematics Topic F - Honours

North Terrace Campus - Semester 2 - 2017

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

  • General Course Information
    Course Details
    Course Code APP MTH 4052
    Course Applied Mathematics Topic F - Honours
    Coordinating Unit School of 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 May only be presented towards some Engineering programs
    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 Staff

    Course Coordinator: Professor Matthew Roughan

    This is the same course as APP MTH 7088 - Applied Mathematics Topic F
    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes

    In 2017 the topic of this course will be Complex network modelling and inference

    Syllabus:

    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".

    Learning Outcomes

    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)
      • Simulation
      • Algorithms
    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 I 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
  • Learning Resources
    Required Resources
    All required materials will be provided.
    Recommended Resources
    "Networks: An Introduction", M.E.J. Newman, Oxford Uni Press, 2010.
    Online Learning
    This course uses MyUni 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 Modes
    This course relies on lectures as the primary delivery mechanism for the material. Written assignments supplement the lectures by providing example problems to enhance the understanding obtained through lectures and provides assessment opportunities for students to gauge their progress and understanding.
    Workload

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    Activity Quantity Workload hours
    Lectures 24 60
    Practicals/Tute 12 30
    Assignments 6 66
    Total 156
    Learning Activities Summary
    Lecture Outline
    1. Basics
      • graph theory basics
      • graph metrics
      • random graph models
      • algorithms on graphs
    2. Advanced Topics
      • graph generalisations: hyper-graphs and meta-graphs
      • graph algebras
    3. Inference
      • sampling from networks
      • inference on graphs: network tomography
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment task Task type When due Weighting Learning outcomes
    Examination Summative Examination period 50% All
    Assignments Formative and summative Weeks 3, 5, 7, 9 and 11 50% All


    Assessment Related Requirements
    An aggregate score of at least 50% is required to pass the course.
    Assessment Detail

    No information currently available.

    Submission
    All written assignments are to be submitted to the lecturer with a signed cover sheet attached. There will be a maximum two week turn-around time on assignments for feedback to students.

    Late assignments will not be accepted, but students may be excused from an assignment for medical or compassionate reasons. In such cases, documentation is required and the lecturer must be notified as soon as possible before the fact.
    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M11 (Honours Mark Scheme)
    GradeGrade reflects following criteria for allocation of gradeReported 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.

  • Student Feedback

    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.

  • Student Support
  • Policies & Guidelines
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