Students
STAT8122 – Time Series
2022 – Session 2, In person-scheduled-weekday, North Ryde
General Information
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| Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit Convenor/Lecturer
Nan Zou
|
|---|---|
| Credit points |
Credit points
10
|
| Prerequisites |
Prerequisites
((Admission to MAppStat or MSc or MScInnovation or GradCertAppStat or GradDipAppStat or MActPrac) and (STAT6110 or STAT806 or STAT810 or STAT8310)) or (Admission to BMathScMAppStat and permission by special approval)
|
| Corequisites |
Corequisites
|
| Co-badged status |
Co-badged status
STAT7122
|
| 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. |
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
General Assessment Information
In this unit, all assessments are individual-based and none of the assessments is "group work".
Assignment Submission
Assignment submission will be online through the iLearn page. Please read the submission statement carefully. You should upload your assignment as a single PDF file. No personalised cover sheet is required for online submissions. Please make sure that each page in your uploaded assignment corresponds to only one A4 page (do not upload an A3 page worth of content as an A4 page in landscape). If you are using an app like Clear Scanner, please make sure that the photos you are using are clear and shadow-free. It is your responsibility to make sure your assignment submission is legible. If there are technical obstructions to your submission online, please email us to let us 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 interests to make frequent submissions of your partially completed work as insurance against technical or other problems near the submission deadline.
Late Assessment Submission Penalty
From 1 July 2022, Students enrolled in Session-based units with written assessments will have the following late penalty applied. Please see https://students.mq.edu.au/study/assessment-exams/assessments for more information.
Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark) will be applied each day a written 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. Submission time for all written assessments is set at 11:55 pm. A 1-hour grace period is 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, students need to submit an application for Special Consideration.
Assessments where Late Submissions will be accepted
In this unit, late submissions will be accepted as follows:
- Assignment 1 – YES, Standard Late Penalty applies
- Assignment 2 – NO, unless Special Consideration is granted
- Assignment 3 – NO, unless Special Consideration is granted
- Final Exam – NO, unless Special Consideration is granted
Final Exam Policy
It is Macquarie University policy not to 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 for an examination at the designated time is because of documented illness or unavoidable disruption. In these special circumstances, you may apply for special consideration via ask.mq.edu.au. If you receive special consideration for the final exam, a supplementary exam will be scheduled in the interval between the regular exam 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 |
|---|---|---|---|
| Assignment 1 | 15% | No | Week 4 |
| Assignment 2 | 15% | No | Week 8 |
| Assignment 3 | 15% | No | Week 12 |
| Final Examination | 55% | No | Formal Examination Period |
Assignment 1
Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 10 hours
Due: Week 4
Weighting: 15%
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
Assignment 2
Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 10 hours
Due: Week 8
Weighting: 15%
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
Assignment 3
Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 10 hours
Due: Week 12
Weighting: 15%
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: Formal Examination Period
Weighting: 55%
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
Lectures and SGTAs
There is one two-hour synchronous lecture and one one-hour SGTA each week. Lectures begin in Week 1 and SGTAs in Week 2. Please consult the timetable for the scheduling of these activities.
Technologies used and required
Lecture material will be placed on iLearn. R is used throughout the unit. R is free and is extensively used for performing statistical analysis.
Textbook
Rob J Hyndman and George Athanasopoulos (2021) Forecasting: principles and practice, 3rd edition, OTexts: Melbourne, Australia.
The online version of this book could be found at https://otexts.com/fpp3/
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 models |
| 7 | Exponential smoothing |
| 8 | Exponential smoothing |
| 9 | ARIMA models |
| 10 | ARIMA models |
| 11 | ARIMA models |
| 12 | Dynamic Regression models |
| 13 | Review |
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:
- Academic Appeals Policy
- Academic Integrity Policy
- Academic Progression Policy
- Assessment Policy
- Fitness to Practice Procedure
- Assessment Procedure
- Complaints Resolution Procedure for Students and Members of the Public
- Special Consideration Policy
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 ask.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
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- Workshops
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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.
Unit information based on version 2022.03 of the Handbook