Students

STAT8122 – Time Series

2025 – Session 2, Online-scheduled-In person assessment, Exam centre within Australia

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Lecturer, Unit Convenor
Assoc. Prof. Tania Prvan
Contact via tania.prvan@mq.edu.au
12 Wally's Walk Level 6 Room 6.29
TBA
Tutor
Mrs Balamehala Pasupathy
Contact via balamehala.pasupathy@mq.edu.au
Credit points Credit points
10
Prerequisites Prerequisites
STAT6110 or STAT8310 or (Admission to GradCertResFSE or GradDipResFSE)
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

This unit is an introduction to Time Series Analysis and Forecasting. This unit introduces methods suitable for forecasting including the decomposition of time series, exponential smoothing methods, ARIMA modelling, and regression with autocorrelated disturbances.

Learning in this unit enhances student understanding of global challenges identified by the United Nations Sustainable Development Goals (UNSDGs) Quality Education; Industry, Innovation and Infrastructure; Climate Action

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: provide an understanding of common statistical methods used in forecasting
  • ULO2: develop computer skills for forecasting time series data
  • ULO3: provide insights into the problems of implementing and operating large scale forecasting systems

General Assessment Information

Requirements to Pass this Unit

To pass this unit you need to:

  • Achieve a total mark equal to or greater than 50% across all assessments

We strongly encourage all students to actively participate in all learning activities. Regular engagement is crucial for your success in this unit, as these activities provide opportunities to deepen your understanding of the material, collaborate with peers, and receive valuable feedback from instructors, to assist in completing the unit assessments. Your active participation not only enhances your own learning experience but also contributes to a vibrant and dynamic learning environment for everyone.

Assignment submission

Assignment submission will be online through the iLearn page. Your name and Student ID should appear on the first page. Submit assignments online via the appropriate assignment link on the iLearn page. A personalised cover sheet is not required with online submissions. Read the submission statement carefully before accepting it as there are substantial penalties for making a false declaration.

  • Assignment submission is via iLearn.
  • Please make sure that your assignment is word processed.
  • You should upload one single PDF file.
  • Please note the quick guide on how to upload your assignments provided on the iLearn page.
  • If there are technical obstructions to your online submission, please email the Unit Convenor to let that person know.

You may submit as often as required prior to the due date/time. Please note that each submission will completely replace any previous submissions. It is in your best interest to make frequent submissions of your partially completed work as insurance against technical or other problems near the submission deadline.

Portfolio submission

Portfolio submission is the same as Assignment Submission for the final submission (comprising of 5 items).

For each Portfolio item there is the opportunity to obtain individual feedback to improve your final submission if your draft portfolio item is submitted on iLearn by the due date. 

Late Assessment Submission Penalty

Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark of the task) will be applied for each day a written report or presentation assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of ‘0’ will be awarded even if the assessment is submitted. The submission time for all uploaded assessments is 11:55 pm. A 1-hour grace period will be provided to students who experience a technical concern. For any late submission of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, please apply for Special Consideration

Assessments where Late Submissions will be accepted 

  • Assignment - YES, Standard Late Penalty applies 
  • Portfolio - YES, Standard Late Penalty Penalty applies

Special Consideration

The Special Consideration Policy aims to support students who have been impacted by short-term circumstances or events that are serious, unavoidable and significantly disruptive, and which may affect their performance in assessment. If you experience circumstances or events that affect your ability to complete the assessments in this unit on time, please inform the convenor and submit a Special Consideration request through https://connect.mq.edu.au.

Final Examination

It is Macquarie University policy to not set early examinations for individuals or groups of students. All students are expected to ensure that they are available until the end of the teaching semester, that is, the final day of the official examination period. The only excuse for not sitting an examination at the designated time is because of documented illness or unavoidable disruption. In these special circumstances, you may apply for special consideration.

If you receive special consideration for the final exam, a supplementary exam will be scheduled in the interval between the regular examination period and the start of the next session. By making a special consideration application for the final exam you are declaring yourself available for a resit during this supplementary examination period and will not be eligible for a second special consideration approval based on pre-existing commitments. Please ensure you are familiar with the policy prior to submitting an application.

Assessment Tasks

Name Weighting Hurdle Due
Portfolio 25% No 19/9/2025
Assignment 25% No 31/10/2025
Final Examination 50% No Examination Period

Portfolio

Assessment Type 1: Portfolio
Indicative Time on Task 2: 15 hours
Due: 19/9/2025
Weighting: 25%

 

A single individual portfolio consisting five items relating to time series, with each item limited to a maximum of two pages, on topics or questions given in the lecture notes. You will be asked to submit the portfolio via iLearn and it will be graded at one specific time. 

 


On successful completion you will be able to:
  • provide an understanding of common statistical methods used in forecasting
  • develop computer skills for forecasting time series data

Assignment

Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 15 hours
Due: 31/10/2025
Weighting: 25%

 

Reinforce and apply the concepts covered in lectures and the skills learned in SGTA sessions, through data analysis.

 


On successful completion you will be able to:
  • provide an understanding of common statistical methods used in forecasting
  • develop computer skills for forecasting time series data
  • provide insights into the problems of implementing and operating large scale forecasting systems

Final Examination

Assessment Type 1: Examination
Indicative Time on Task 2: 20 hours
Due: Examination Period
Weighting: 50%

 

An invigilated final examination to be scheduled in the university examination period.

 


On successful completion you will be able to:
  • provide an understanding of common statistical methods used in forecasting
  • develop computer skills for forecasting time series data
  • provide insights into the problems of implementing and operating large scale forecasting systems

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Writing Centre for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation

Delivery and Resources

Week 1 classes

There is a 2 hour lecture in Week 1.

Delivery

There is a 2 hour lecture and a 1 hour SGTA each week. SGTAs begin in Week 2. Please consult the timetable for the scheduling of these activities. The timetable for classes can be fount on the University website at: https://publish.mq.edu.au/. Enrolment can be managed using eStudent at: https://students.mq.edu.au/support/technology/systems/estudent.

In addition to the two hour lecture there are online resources including videos which should be viewed prior to the lecture.

Technologies used and required

Lecture material will be placed on iLearn. The statistical package R will be used. SGTA SGTAs are held in computing labs and allow you to practice techniques learnt in lectures and from above mentioned online resources.  

Text book

Rob J Hyndman and George Athanasopoulos (2021) Forecasting: principles and practice, 3rd edition, OTexts: Melbourne, Australia. The online version of this book is found at https://otexts.com/fpp3/.

Methods of communication

We will communicate with you via your university email and through announcements on iLearn. Queries to convenors can either be placed on the iLearn discussion board or sent to the unit convenor via the contact email on iLearn.

Unit Schedule

 

Week Topic
1 Introduction
2 Time series graphics
3 Time series decomposition
4 Time series features
5 The forecaster's toolbox
6 Time series regression moodels
7 Exponential smoothing
8 Exponential smoothing
9 ARIMA models
10 ARIMA models
11 ARIMA models
12 Dynamic regression models
13 Revision

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:

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.

To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct

Results

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 connect.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Academic Integrity

At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

Academic Success

Academic Success provides resources to develop your English language proficiency, academic writing, and communication skills.

The Library provides online and face to face support to help you find and use relevant information resources. 

Student Services and Support

Macquarie University offers a range of Student Support Services including:

Student Enquiries

Got a question? Ask us via the Service Connect Portal, or contact Service Connect.

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/

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.

Changes from Previous Offering

To enable students more time to focus on learning, understanding and reflecting on the content of our unit we have revised the assessment structure as follows. There are now only three assessments: a skills assessment, report and final exam. Although no marks are associated with attendance, all activities provide you with key content designed to help you understand content and complete the assessments.


Unit information based on version 2025.06 of the Handbook