- Class Number 6215
- Term Code 3360
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- Dr William Lim
- Dr William Lim
- Class Dates
- Class Start Date 24/07/2023
- Class End Date 27/10/2023
- Census Date 31/08/2023
- Last Date to Enrol 31/07/2023
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 Data Analytics Principles subject under the Actuaries Institute’s Actuary program. Such exemption depends on the grades attained in the subject.
Upon successful completion, students will have the knowledge and skills to:
- Explain where and how their analytical work can add value to the business environment and strategy.
- Source, interpret, evaluate, prepare and justify data for modelling.
- Select, compare and justify appropriate predictive analytic techniques for a given business problem.
- Apply predictive analytic techniques to solve complex estimation and classification problems.
- Evaluate and compare performance of different models.
- Communicate findings to a range of audiences.
This course covers the relevant parts of the Actuaries Institute Actuary Program. The course will address current issues of interest and current approaches to data analytics, using practical examples and case studies.
Examination Material or equipment
Centrally scheduled examinations through Examinations, and will be timetabled prior to the examination period. Please check ANU Timetabling for further information.
Comprehensive lecture slides will be made available on Wattle. The use of R and Word is required for the completion of all assessments 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 is 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 specified in lecture time and on Wattle. Other relevant reading and reference material will be made available on Wattle throughout the semester.
Students will be given feedback in the following forms in this course:
· Self-study feedback in tutorials.
· Self-study feedback from quizzes/tasks provided for this purpose.
· Group in class feedback on performance in quizzes, and assignments.
· Individual feedback on student performance in assessment tasks is available on request from the lecturer; please make an appointment to request this.
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). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.
Support for Students
The University offers a number of support services for students. Information on these is available online from http://students.anu.edu.au/studentlife/
Communication via Email
If I, or anyone in the School, College or University administration, need to contact you, we will do so via your official ANU student email address, which you need to check regularly. If you have any questions for the teaching and course convenor make sure you email them using your ANU email address. Emails from personal email accounts will not be answered.
Students are expected to check the Wattle site for announcements about this course, e.g. changes to timetables or notifications of cancellations.
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.
Your final mark for the course will be based on the raw marks allocated for each of your assessment items. However, your final mark may not be the same number as produced by that formula, as marks may be scaled. Any scaling applied will preserve the rank order of raw marks (i.e. if your raw mark exceeds that of another student, then your scaled mark will exceed the scaled mark of that student), and may be either up or down.
In assignments and exams, students must appropriately reference any results, words or ideas that they take from another source which is not their own. A guide can be found
ACST4062 shares the same lecture content and assignments with ACST8032, however these cohorts may have separate tutorials and different assessments. The different cohorts of students will also be treated separately in grading and any scaling that is applied.
|Week/Session||Summary of Activities||Assessment|
|1||Topic: 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|
|7||Shrinkage techniques||Assignment 1 due|
|9||Gradient boosting method|
|10||Neural network and others|
|11||Business outcomes and communication II||Assignment 2 due|
|12||Modelling process and exam preparation|
Tutorials will be held on campus weekly (starting from week 2). ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time.
Tutorial registration will be available two weeks prior to the beginning of the semester and will close at the end of week 1. More details can be found on the Timetable webpage (https://www.anu.edu.au/students/program-administration/timetabling)
|Assessment task||Value||Due Date||Return of assessment||Learning Outcomes|
|Quiz||0 %||25/08/2023||25/08/2023||2, 3, 4, 5|
|Assignment 1||20 %||18/09/2023||03/10/2023||1, 2, 4, 5, 6|
|Assignment 2||20 %||20/10/2023||01/11/2023||1, 2, 3, 4, 5, 6|
|Final exam||60 %||02/11/2023||30/11/2023||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 Integrity 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 Academic Skills 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.
Course content delivery will take the form of weekly pre-recorded lectures (available via echo360 on Wattle), weekly on-campus workshops (recorded and available via echo360 on Wattle), and weekly on-campus tutorials. Weekly consultations with the lecturer and the tutor(s) will be conducted over Zoom.
The final examination will be a three-hour on-campus invigilated exam. The final examination will be conducted in on-campus computer labs where students can access R and Words. Students are allowed to refer to all paper-based materials. The final exam is a compulsory piece of assessment and worth 60% of the total assessment. The final exam will be held during the exam period with details to be advised no later than teaching week 10 of the semester.
Assessment Task 1
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.
Due date: Friday 25th August
Assessment Task 2
Learning Outcomes: 1, 2, 4, 5, 6
Students are expected to complete this assignment individually. This assignment assesses topics covered from Week 1 to Week 6 (inclusive). Students are required to use R to perform data analysis and modelling, and prepare a written business report. This assignment is worth 20% of the total assessment. This assignment will be made available on 28 August (Week 6), due on 18 September (Week 7) and returned on 3 October (Week 9). Assignment submission will consist of a Word or PDF (Portable Document Format) report uploaded to Wattle to the relevant Assignment activity through Turnitin. Students will be required to electronically sign a declaration as part of the submission of the assignment. Feedback will be given to the whole class in lecture on common errors; individual feedback may be given with marks, may be available from the tutor/lecturer by appointment.
Due date: Monday 18 September
Assessment Task 3
Learning Outcomes: 1, 2, 3, 4, 5, 6
Students are expected to complete this assignment individually. This assignment assesses topics covered from Week 1 to Week 9 (inclusive). Students are required to use R to perform data analysis and modelling, evaluate and transform information, and prepare a written business report. This assignment is worth 20% of the total assessment. This assignment will be made available on 29 September (Week 8), due on 20 October (Week 11), returned on 1 November. Assignment submission will consist of a Word or PDF (Portable Document Format) report uploaded to Wattle to the relevant Assignment activity through Turnitin. Students will be required to electronically sign a declaration as part of the submission of the assignment. Feedback will be given to the whole class in lecture on common errors; individual feedback may be given with marks, may be available from the tutor/lecturer by appointment.
Due date: Friday 20th October
Assessment Task 4
Learning Outcomes: 1, 2, 3, 4, 5, 6
The final examination will be a three-hour on-campus invigilated exam with a mix of short and long answers questions. The final examination will be conducted in on-campus computer labs where students can access R and Words. Students are allowed to refer to all paper-based materials. The final exam is a compulsory piece of assessment and worth 60% of the total assessment. The final exam will be held during the exam period with details to be advised no later than teaching week 10 of the semester.
Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.
The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.
The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.
The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.
Assignment submission will consist of a Word or PDF (Portable Document Format) report uploaded to Wattle to the relevant Assignment activity through Turnitin. 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.
There are no hardcopy submissions in the course.
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.
The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.
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.
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 Access 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 all ANU students