Unit convenor and teaching staff |
Unit convenor and teaching staff
Kenneth Beath
Contact via ken.beath@mq.edu.au
E4A 507
Friday 2-4
Thomas Fung
Contact via thomas.fung@mq.edu.au
E4A 530
Monday 2 - 4 pm
Gillian Heller
Contact via gillian.heller@mq.edu.au
E4A 533
Thursday 12-2 pm
Unit Convenor
Jun Ma
Contact via jun.ma@mq.edu.au
E4A511
TBA
Maurizio Manuguerra
Contact via maurizio.manuguerra@mq.edu.au
E4A 452
TBA
Barry Quinn
Contact via barry.quinn@mq.edu.au
E4A535
Tuesday 5-6, Thursday 2-3
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Credit points |
Credit points
4
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Prerequisites |
Prerequisites
Admission to MRes
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Corequisites |
Corequisites
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Co-badged status |
Co-badged status
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Unit description |
Unit description
This unit covers selected topics on modern statistical methods including statistical modelling, computational statistics, bio- and medical statistics, statistical models in finance, modelling dependence and point processes. These topics are hot research areas of statistics. The topics will be delivered by reading research papers, discussions and presentations. Students are also required to attend department research seminars. Each topic will be taught in two weeks and then assessed by the lecturer delivering the topic.
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Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
On successful completion of this unit, you will be able to:
Name | Weighting | Due |
---|---|---|
Topic 1 | 15% | Mar 11th |
Topic 2 | 15% | Mar 25th |
Topic 3 | 15% | April 8th |
Topic 4 | 15% | May 6th |
Topic 5 | 15% | June 6th |
Topic 6 | 15% | May 20th |
Statistics department seminar | 10% | TBA |
Due: Mar 11th
Weighting: 15%
This topic will be on "Statistical modelling and model selection". Each topic will be assessed by the lecturer of that topic. Each topic weights 15% towards the final assessment. Topic assessment is based on presentation (13%) and participation (2%). Three core criteria will be used to assess students’ work:
(1) Knowledge Development: Understanding of key ideas and concepts.
(2) Application: Ability to apply statistical concepts to actual problems.
(3) Presentation: The extent to which work has been written and/or presented in a manner consistent with accepted academic standards.
Performance in relation to each of these criteria will be assessed against established standards.
Due: Mar 25th
Weighting: 15%
This topic will be on "Computational statistics, including EM, mixture distribution, LASSO". For assessment see topic 1
Due: April 8th
Weighting: 15%
This topic will be on "Point processes, including homogeneous and non-homogeneous Poisson processes and applications". For assessment see topic 1
Due: May 6th
Weighting: 15%
This topic will be on "Statistical models in finance, including ARCH & GARCH models". For assessment see topic 1
Due: June 6th
Weighting: 15%
This topic will be on "Bio- and medical statistics, including Cox model, censorings, recurrent events, multi-states". For assessment see topic 1
Due: May 20th
Weighting: 15%
This topic will be on "Time series and related CLT". For assessment see topic 1
Due: TBA
Weighting: 10%
Students are required to attend the research seminars of Statistics Department. Their attendance and performance (asking questions and participation in discussions) will be used for this assessment.
Lectures
Lectures begin in Week 1. Students should attend one 3-hour session per week. Papers and reading materials for each topic will be made available via iLearn. Students should read these materials prior to the lectures.
Each topic will last for two weeks. In the first week, the lecturer will give a brief introduction to the materials covered in that topic and introduce students to the papers that will be discussed. Each student will be given three papers to read. However, each student will be required to present one paper in the class in the second week. Students are encouraged to participate in presentations, i.e. ask questions and involve in discussions.
Department research seminars
Students are also required to attend the research seminars of Statistics Department.
Changes from previous offerings
None
Technologies used and required
None
WEEK |
LECTURE TOPIC |
Lecturer
|
W1-2
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Statistical modelling and model selection |
Gillian Heller |
W3-4
|
Computational statistics, including EM, mixture distribution, LASSO etc |
Jun Ma |
W5-6
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Point processes, including homogeneous and non-homogeneous Poisson processes and applications |
Maurizio Manuguerra |
Semester break
|
||
W7-8
|
Statistical models in finance, including ARCH & GARCH models etc |
Thomas Fung |
W9-10
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Bio- and medical statistics, including Cox model, censorings, recurrent events, multi-states |
Ken Beath |
W11-12
|
Time series and related CLT |
Barry Quinn |
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Academic Honesty Policy http://mq.edu.au/policy/docs/academic_honesty/policy.html
Assessment Policy http://mq.edu.au/policy/docs/assessment/policy.html
Grading Policy http://mq.edu.au/policy/docs/grading/policy.html
Grade Appeal Policy http://mq.edu.au/policy/docs/gradeappeal/policy.html
Grievance Management Policy http://mq.edu.au/policy/docs/grievance_management/policy.html
Disruption to Studies Policy http://www.mq.edu.au/policy/docs/disruption_studies/policy.html The Disruption to Studies Policy is effective from March 3 2014 and replaces the Special Consideration Policy.
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