Notice
As part of Phase 3 of our return to campus plan, most units will now run tutorials, seminars and other small group activities on campus, and most will keep an online version available to those students unable to return or those who choose to continue their studies online.
To check the availability of face-to-face and online activities for your unit, please go to timetable viewer. To check detailed information on unit assessments visit your unit's iLearn space or consult your unit convenor.
Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit Convenor
Xian Zhou
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Credit points |
Credit points
10
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Prerequisites |
Prerequisites
STAT810 or STAT8310 or STAT806
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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 provides sophisticated statistical and probabilistic models for survival, sickness, insurance losses and other actuarial problems based on survival data. Techniques of survival analysis are used to estimate survival and loss distributions and evaluate risk factors in actuarial applications. Methods of both nonparametric and parametric estimation are utilised. Advanced models based on Markov chains and processes will be introduced to capture the features of stochastic transitions between different survival or loss states and to estimate the transition rates. Methods for valuing cashflows that are contingent upon multiple transition events and methods of projecting and valuing such expected cashflows will also be covered. Students gaining a weighted average of credit across all of ACST8084, ACST8085 and the CS2-related components of the assessment in ACST8086 (minimum mark of 60% on all three components) will satisfy the requirements for exemption from the professional subject CS2 of the Actuaries Institute. |
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:
Assessment criteria for all assessment tasks will be provided on the unit iLearn site.
It is the responsibility of students to view their marks for each within-session-assessment on iLearn within 20 days of posting. If there are any discrepancies, students must contact the unit convenor immediately. Failure to do so will mean that queries received after the release of final results regarding assessment tasks (not including the final exam mark) will not be addressed.
Late submissions and extensions
Tasks 10% or less – No extensions will be granted. Students who have not submitted the task prior to the deadline will be awarded a mark of 0 for the task, except for cases in which an application for special consideration is made and approved.
Tasks above 10% - No extensions will be granted. There will be a deduction of 10% of the total available marks made from the total awarded mark for each 24 hour period or part thereof that the submission is late (for example, 25 hours late in submission – 20% penalty). This penalty does not apply for cases in which an application for special consideration is made and approved. No submission will be accepted after solutions have been posted.
Name | Weighting | Hurdle | Due |
---|---|---|---|
Class Test | 20% | No | 21/04/21 |
Assignment | 20% | No | 02/06/21 |
Final Exam | 60% | No | Examination Period |
Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 17 hours
Due: 21/04/21
Weighting: 20%
The test will be approximately 120 minutes, to be held during class time.
Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 20 hours
Due: 02/06/21
Weighting: 20%
Problem-solving questions requiring detailed solutions using the statistical package R.
Assessment Type 1: Examination
Indicative Time on Task 2: 28 hours
Due: Examination Period
Weighting: 60%
The final examination will be closed book, a three-hour written paper with ten minutes reading time, to be held during the University Examination period.
1 If you need help with your assignment, please contact:
2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation
Classes
Unit Web Page
Technology Used and required
Required and Recommended Texts and/or Materials
Week 1: Probability models (revision); Survival analysis
Week 2: Estimation of survival distributions
Week 3: Variance estimation and confidence intervals
Week 4: Cox proportional hazards models
Week 5: Cox proportional hazards models; Stochastic processes;
Week 6 (last week before semester break): Markov chains
Week 7 (first week after semester break): Class test; Markov chains
Week 8: Markov jump processes
Week 9: Markov jump processes
Week 10: Applications of Markov processes
Week 11: Applications of Markov processes
Week 12: Multi-state insurance models and multiple decrement tables
Week 13: Assignment and Revision
Note: This is only a tentative schedule. The actual schedule will be adjusted from time to time in accordance with the progress of lectures.
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Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.
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Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to help you improve your marks and take control of your study.
The Library provides online and face to face support to help you find and use relevant information resources.
Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.
For all student enquiries, visit Student Connect at ask.mq.edu.au
If you are a Global MBA student contact globalmba.support@mq.edu.au
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When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.
Unit information based on version 2021.04 of the Handbook