• Class Number 8623
  • Term Code 3060
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
    • William Lim
    • William Lim
  • Class Dates
  • Class Start Date 27/07/2020
  • Class End Date 30/10/2020
  • Census Date 31/08/2020
  • Last Date to Enrol 03/08/2020
SELT Survey Results

This course aims to extend actuarial students' knowledge of modern analytical tools and techniques beyond those introduced in introductory actuarial courses. It further aims to to teach students how to apply this knowledge in real-life business settings, preparing them for more complex and practice specific applications which will be taught in future courses in their actuarial education.

This subject provides the opportunity for exemption from the requirements of the Core Data & Statistical Analysis subject under the Actuaries Institute’s Associate program. Such exemption depends on the grades attained in the subject.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. explain where and how their analytical work can add value to the business environment and strategy;
  2. source, interpret, evaluate and prepare data for modelling;
  3. select and justify appropriate predictive analytic techniques for a given business problem;
  4. apply predictive analytic techniques to solve estimation and classification problems;
  5. evaluate and compare performance of different models; and
  6. communicate findings to a range of audiences.

Examination Material or equipment

Due to the impacts of COVID-19, the final exam will likely be held as a take home exams with limited timeframes and using the Proctorio online invigilation software. Students will need to have access to R and Word. Further information on examination material will be provided to students on Wattle. The final exam will be held in the exam period with details to be advised no later than teaching week 12 of the semester.

Required Resources

The use of R and Word is required for the completion of all assessment in this course. You are assumed to have experience in R and Word from previous courses. R and Word may be used on campus (if computer labs are open) or on the students’ personal computers or laptops. Word are available for free to ANU students through Microsoft Office 365. R and its user interface R Studio are as freely available at the links provided.

We will be using some materials from the following books throughout the semester:

(1) R for Data Science , by Wickham and Grolemund

(2) An Introduction to Statistical Learning , by James, Witten, Hastie and Tibshirani

(3) The Elements of Statistical Learning , by Hastie, Tibshirani and Friedman

The electronic versions of these books are freely available online from the corresponding authors. The relevant readings for each week will be provided in lecture time and on Wattle. Other relevant reading and reference material will be made available on Wattle throughout the semester.

Staff Feedback

  • Whole of class feedback in-lecture and via discussion forums
  • Written comments on assignment submissions
  • Individual meetings with the course convenor as organised by students

Student Feedback

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.

Other Information

Information on how the class schedule will run due to remote learning is available on Wattle.

Class Schedule

Week/Session Summary of Activities Assessment
1 Introduction and data exploration
2 Data manipulation and visualisation
3 Modelling principles and processes I
4 Modelling principles and processes II
5 Business outcomes and communication I Quiz
6 Linear regression and GLM Assignment 1 due (teaching break week 2)
7 Shrinkage techniques
8 Tree-based methods
9 Gradient boosting method
10 Neural network and others
11 Business outcomes and communication II Assignment 2 due
12 Modelling process and exam preparation

Tutorial Registration

See information on Wattle for how the class is structured for remote learning.

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Quiz 0 % 28/08/2020 28/08/2020 2, 3, 4, 5
Assignment 1 20 % 18/09/2020 02/10/2020 1, 2, 3, 4, 5, 6
Assignment 2 20 % 23/10/2020 06/11/2020 1, 2, 3, 4, 5, 6
Final exam 60 % 05/11/2020 03/12/2020 1, 2, 3, 4, 5, 6

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details


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:

Assessment Requirements

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 Academic Integrity . 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

Value: 0 %
Due Date: 28/08/2020
Return of Assessment: 28/08/2020
Learning Outcomes: 2, 3, 4, 5


This consists of a set of problems that will be made available on Wattle in Week 5. The problems will relate to material in Week 1 to Week 4 only (inclusive). The solution is immediately available to students on Wattle upon submission. This quiz is solely for self-assessment purposes and will not contribute towards students' final grades.

Assessment Task 2

Value: 20 %
Due Date: 18/09/2020
Return of Assessment: 02/10/2020
Learning Outcomes: 1, 2, 3, 4, 5, 6

Assignment 1

This assignment covers LO 2, 3, 4, and 5 and is worth 20% of the total assessment. The assignment will be made available on 28 Aug (Week 5) and due on 18 September (Teaching break week 2).

Assessment Task 3

Value: 20 %
Due Date: 23/10/2020
Return of Assessment: 06/11/2020
Learning Outcomes: 1, 2, 3, 4, 5, 6

Assignment 2

This assignment covers LO 1, 2, 3, 4, 5, and 6 and is worth 20% of the total assessment. The assignment will be made available on 2 October (Week 8) and due on 23 October (Week 11).

Assessment Task 4

Value: 60 %
Due Date: 05/11/2020
Return of Assessment: 03/12/2020
Learning Outcomes: 1, 2, 3, 4, 5, 6

Final exam

This exam covers LO 1, 2, 3, 4, 5, and 6 and is worth 60% of the total assessment. The final assessment will be held in the exam period with details to be advised no later than teaching week 12 of the semester.

Academic Integrity

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.

Online Submission

Assignment submission will consist of a Word or PDF (Portable Document Format) report uploaded to Wattle to the relevant Assignment activity. 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.

Exam submission will consist of a Word or PDF (Portable Document Format) report uploaded to Wattle to the relevant Examination activity. You will be required to electronically sign a declaration as part of the submission of your exam. Please keep a copy of the exam for your records.

Hardcopy Submission

All assessment submission in the course is online (see above).

Late Submission

No submission of assignments without an extension after the due date will be permitted. If an assignment is not submitted by the due date, a mark of 0 will be awarded.

Referencing Requirements

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.

Returning Assignments

Assignment mark and comment will be returned via Wattle or email.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted 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.

Resubmission of Assignments

No resubmission of assignments is permitted.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

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).

William Lim

Research Interests

My primary research interests are in the areas of individual decisions relating to investment and retirement income.

William Lim

Tuesday 15:00 16:00
Wednesday 08:00 09:00
By Appointment
William Lim

Research Interests

William Lim

Tuesday 15:00 16:00
Wednesday 08:00 09:00
By Appointment

Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions