- Class Number 7472
- Term Code 2960
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- Dr Borek Puza
- Dr Borek Puza
- Class Dates
- Class Start Date 22/07/2019
- Class End Date 25/10/2019
- Census Date 31/08/2019
- Last Date to Enrol 29/07/2019
This course covers the fundamental concepts of: Bayesian statistics, including estimation, prediction, hypothesis testing, and decision theory; time series analysis, including estimation and prediction based on ARIMA models; credibility theory, including limited fluctuation credibility theory and the Buhlmann-Straub model; several run-off techniques for estimating an outstanding claims reserve; and Monte Carlo techniques, including the inverse transformation method, the polar method, and Monte Carlo integration.
Upon successful completion, students will have the knowledge and skills to:
- Explain the fundamental concepts of Bayesian statistics and use these concepts to calculate Bayesian estimators (including credibility estimators).
- Define and apply the main concepts underlying the analysis of time series models.
- Describe and apply techniques for analysing a delay (or run-off) triangle and projecting the ultimate position.
- Explain and apply the concepts of “Monte Carloâ€? simulation using a series of pseudo-random numbers.
If time permits, the lecturer may illustrate selected topics by discussing relevant examples from papers that he has published. New material in these examples will not be assessable.
Examination Material or equipment
For both exams students should bring a scientific, non-programmable calculator.
The course material consists of lecture notes, solutions to problems in the lecture notes, tutorials plus solutions, and several past exams plus solutions. This material will progressively be made available on Wattle. From time to time, other material will be posted on Wattle, such as corrections and additional examples. Students should check the top of the Wattle page every day or two for Notices regarding such new material and other information.
Students will be given feedback in the following forms in this course:
· written comments
· verbal comments
· feedback to whole class, groups, individuals, focus group etc.
ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.
As a further academic integrity control, students may be selected for a 15 minute individual oral examination of their written assessment submissions. Any student identified, either during the current semester or in retrospect, as having used ghost writing services will be investigated under the University’s Academic Misconduct Rule.
|Week/Session||Summary of Activities||Assessment|
|1||Bayesian Statistics, Lectures|
|2||Bayesian Statistics, Lectures, Tutorial|
|3||Bayesian Statistics, Lectures, Tutorial|
|4||Bayesian Statistics, Lectures, Tutorial|
|5||Time Series Analysis, Lectures, Tutorial|
|6||Time Series Analysis, Lectures, Tutorial||Mid-semester examination (possibly this week)|
|7||Credibility Theory, Lectures, Tutorial||Mid-semester examination (possibly this week)|
|8||Credibility Theory, Lectures, Tutorial|
|9||Credibility Theory, Lectures, Tutorial|
|10||Run-Off Techniques, Lectures, Tutorial|
|11||Monte Carlo Simulation, Lectures, Tutorial|
|12||Gibbs Sampling, Revision, Lectures, Tutorial|
Please see Wattle for tutors’ information. Tutorial signup for this course will be done via the Wattle website. Detailed information about signup times will be provided on Wattle. When tutorials are available for enrolment, follow these steps:
1. Log on to Wattle, and go to the course site.
2. Click on the link “Tutorial enrolment”
3. On the right of the screen, click on the tab “Become Member of ……” for the tutorial class you wish to enter.
4. Confirm your choice
If you need to change your enrolment, you will be able to do so by clicking on the tab “Leave group…” and then re-enrol in another group. You will not be able to enrol in groups that have reached their maximum number. Please note that enrolment in ISIS must be finalised for you to have access to Wattle.
|Assessment task||Value||Due Date||Return of assessment||Learning Outcomes|
|Mid-semester exam||30 %||26/08/2019||04/10/2019||1|
|Final exam||70 %||31/10/2019||28/11/2019||1, 2, 3, 4|
ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:
The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.
Moderation of Assessment
Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.
Centrally administered examinations through Examinations, Graduations & Prizes will be timetabled prior to the examination period. Please check ANU Timetabling for further information. Exam scripts will not be returned.
Assessment Task 1
Learning Outcomes: 1
The quiz is for self-assessment purposes only and does not count towards your final grade. It will be made available on Wattle on 6 August and students should complete it by 13 August, when the solutions will be posted on Wattle. If students have any issues with the solutions, they should discuss these with the lecturer, who will, on 20 August or soon thereafter, aim to clarify these issues in lectures.
Assessment Task 2
Learning Outcomes: 1
This exam is closed-book with the only permitted materials being a non-programmable calculator and an unannotated paper-based dictionary (with no approval required). A formula sheet will be attached to the exam paper. Students will be able to view the sheet two weeks in advance on Wattle. The exam is redeemable in favour of the final exam. Thus if you do worse in the mid-semester exam, or do not sit it, your final exam will count 100%.
Assessment Task 3
Learning Outcomes: 1, 2, 3, 4
This exam is closed-book with the only permitted materials being a non-programmable calculator and an unannotated paper-based dictionary (with no approval required). A formula sheet will be attached to the exam paper. Students will be able to view the sheet two weeks in advance on Wattle. In the final exam, there will be one extra question for STAT4036 and STAT8036 students, which STAT3036 students will not need to do. This extra question will be the only difference in assessment between the three courses.
Academic integrity is a core part of the ANU culture as a community of scholars. At its heart, academic integrity is about behaving ethically, committing to honest and responsible scholarly practice and upholding these values with respect and fairness.
The ANU commits to assisting all members of our community to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to be familiar with the academic integrity principle and Academic Misconduct Rule, uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with.
The Academic Misconduct Rule is in place to promote academic integrity and manage academic misconduct. Very minor breaches of the academic integrity principle may result in a reduction of marks of up to 10% of the total marks available for the assessment. The ANU offers a number of online and in person services to assist students with their assignments, examinations, and other learning activities. Visit the Academic Skills website for more information about academic integrity, your responsibilities and for assistance with your assignments, writing skills and study.
You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.
For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.
Please note that this course has no assignments.
Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.
Extensions and Penalties
Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. The Course Convener may grant extensions for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.
Distribution of grades policy
Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.
Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.
Support for students
The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).
- ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
- ANU Diversity and inclusion for students with a disability or ongoing or chronic illness
- ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
- ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
- ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
- ANUSA supports and represents undergraduate and ANU College students
- PARSA supports and represents postgraduate and research students
Bayesian statistics, confidence estimation, paradoxes in probability and statistics
Dr Borek Puza