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Students

ECON2041 – Introductory Econometrics

2026 – Session 1, 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, tutor
Chris Heaton
chris.heaton@mq.edu.au
Contact via chris.heaton@mq.edu.au
04EaR-444
TBA on iLearn
Tutor
Syed Atif
syed.atif@mq.edu.au
Contact via syed.atif@mq.edu.au
Tutor
Rerotlhe Brandon Basele
rerotlhebrandon.basele@mq.edu.au
Contact via rerotlhebrandon.basele@mq.edu.au
Tutor
Fazeel Mohamed Jaleel
fazeel.jaleel@mq.edu.au
Contact via fazeel.jaleel@mq.edu.au
Credit points Credit points
10
Prerequisites Prerequisites
STAT1250 or STAT1170 or STAT1371 or FOSE1005 or FOSE1015 or FOSE1025​ or COMP1000
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

This unit introduces the main econometric techniques used by businesses and economists in the analysis of economic relationships, marketing and finance. These tools are critical building blocks for students to make the link between data and established evidence. The unit focuses on estimation and hypothesis testing, simple and multiple regression, prediction and the interpretation and evaluation of regression models within the classical linear regression model.

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: Analyse and apply key statistical concepts, including probability distributions, parameters and estimators, the sampling distribution of an estimator, point and interval estimation, and hypothesis testing.
  • ULO2:  Specify, estimate and interpret a regression model. 
  • ULO3: Summarise and interpret the estimation results, and draw valid inferences utilising hypothesis tests.
  • ULO4: Critically evaluate the assumptions of a classical (or standard) regression model and the consequences of a violation of the assumptions.
  • ULO5: Employ an econometric software program to solve an econometric problem.

General Assessment Information

Late Submission Penalties

If you submit your assessment late, 5% of the total possible marks will be deducted for each day (including weekends), up to 7 days. Submissions more than 7 days late will receive a mark of 0.

Example 1 (out of 100):

If you score 85/100 but submit 20 hours late, you will lose 5 marks and receive 80/100.

Example 2 (out of 30):

If you score 27/30 but submit 20 hours late, you will lose 1.5 marks and receive 25.5/30.

Extensions

Automatic short extension: Some assessments are eligible for automatic short extension. You can only apply for an automatic short extension before the due date.

Special Consideration: If you need more time due to serious issues and for any assessments that are not eligible for Short Extension, you must apply for Special Consideration. Need help? Review the Special Consideration page for further details.

Assessment Tasks

Name Weighting Hurdle Due Groupwork/Individual Short Extension AI assisted?
Skills development: Knowledge quiz 20% No Week 6 Individual No Observed
Skills development: Econometric problem solving 30% No 25/05/2026 Individual Yes Open AI
Formal examination 50% No Exam period Individual No Observed

Skills development: Knowledge quiz

Assessment Type 1: Problem-based task
Indicative Time on Task 2: 20 hours
Due: Week 6
Weighting: 20%
Groupwork/Individual: Individual
Short extension 3: No
AI assisted?: Observed

The purpose of this knowledge quiz is to ensure your acquisition of the concepts and skills that are foundational to applied econometrics. You will be given a quiz before the mid session break and will receive feedback on your progress.

 

Skills in focus:

  • Discipline knowledge
  • Critical thinking and problem solving

Deliverable(s): In-class quiz

 

Individual assessment
On successful completion you will be able to:
  •  Specify, estimate and interpret a regression model. 
  • Summarise and interpret the estimation results, and draw valid inferences utilising hypothesis tests.
  • Employ an econometric software program to solve an econometric problem.

Skills development: Econometric problem solving

Assessment Type 1: Problem-based task
Indicative Time on Task 2: 25 hours
Due: 25/05/2026
Weighting: 30%
Groupwork/Individual: Individual
Short extension 3: Yes
AI assisted?: Open AI

The purpose of this assessment is to develop an understanding of econometric techniques and theory and how they can be applied to solve practical problems in economics. You will complete a set of questions requiring both calculation and short written answers. It will be based on material covered in the lectures prior to the submission deadline.

 

Skills in focus:

  • Critical thinking and problem solving
  • Discipline knowledge

Deliverable(s): Short answer submission to problem set

 

Individual assessment.
On successful completion you will be able to:
  •  Specify, estimate and interpret a regression model. 
  • Summarise and interpret the estimation results, and draw valid inferences utilising hypothesis tests.
  • Employ an econometric software program to solve an econometric problem.

Formal examination

Assessment Type 1: Examination
Indicative Time on Task 2: 35 hours
Due: Exam period
Weighting: 50%
Groupwork/Individual: Individual
Short extension 3: No
AI assisted?: Observed

The purpose of this assessment is for you to demonstrate the expertise you have gained in this unit.

You will participate in a 2-hour, on campus, closed-book exam held during the University Examination period.

Important information about the exam will be made available on the unit iLearn page. You should also review the MQ Exams website for general tips. 

Deliverable(s): Formal exam

Individual assessment
On successful completion you will be able to:
  • Analyse and apply key statistical concepts, including probability distributions, parameters and estimators, the sampling distribution of an estimator, point and interval estimation, and hypothesis testing.
  • Summarise and interpret the estimation results, and draw valid inferences utilising hypothesis tests.
  • Critically evaluate the assumptions of a classical (or standard) regression model and the consequences of a violation of the assumptions.

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.

3 An automatic short extension is available for some assessments. Apply through the Service Connect Portal.

Delivery and Resources

See iLearn

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.

Unit information based on version 2026.03 of the Handbook