Students

STAT7122 – Time Series

2021 – Session 2, Special circumstances, Exam centre within Australia

Session 2 Learning and Teaching Update

The decision has been made to conduct study online for the remainder of Session 2 for all units WITHOUT mandatory on-campus learning activities. Exams for Session 2 will also be online where possible to do so.

This is due to the extension of the lockdown orders and to provide certainty around arrangements for the remainder of Session 2. We hope to return to campus beyond Session 2 as soon as it is safe and appropriate to do so.

Some classes/teaching activities cannot be moved online and must be taught on campus. You should already know if you are in one of these classes/teaching activities and your unit convenor will provide you with more information via iLearn. If you want to confirm, see the list of units with mandatory on-campus classes/teaching activities.

Visit the MQ COVID-19 information page for more detail.

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Unit Convenor/Lecturer
Tania Prvan
Contact via tania.prvan@mq.edu.au
12 Wally's Walk Room 629
Please refer to iLearn
Lecturer
Nan Zou
Contact via nan.zou@mq.edu.au
12 Wally's Walk Room 706
Please refer to iLearn
Credit points Credit points
10
Prerequisites Prerequisites
Admission to MRes
Corequisites Corequisites
STAT7310 or STAT710
Co-badged status Co-badged status
STAT8122
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 modeling, 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

There is no "group work" assessment in this unit.

Each assignment must be word processed and submitted online via iLearn by the due date. Late submission requires an approved Special Consideration.

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 Exam 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 Exam 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

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.

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

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. 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 ARIMA models
9 Dynamic Regression Models
10 Forecasting hierarchical and grouped time series
11 Advanced forecasting methods
12 Some practical forecasting issues
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 ask.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Student Support

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

Learning Skills

Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to help you improve your marks and take control of your study.

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

Student Services and Support

Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.

Student Enquiries

For all student enquiries, visit Student Connect at ask.mq.edu.au

If you are a Global MBA student contact globalmba.support@mq.edu.au

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 2021.02 of the Handbook