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Course profile

Mathematical Techniques for Economics (ECON7150)

Study period
Sem 2 2025
Location
St Lucia
Attendance mode
In Person

Course overview

Study period
Semester 2, 2025 (28/07/2025 - 22/11/2025)
Study level
Postgraduate Coursework
Location
St Lucia
Attendance mode
In Person
Units
2
Administrative campus
St Lucia
Coordinating unit
Economics School

This course will focus on the application of differential & integral calculus as well as matrix algebra to economic models. Simple unconstrained optimisation will be studied. The course will also introduce some aspects of multi-variate analysis.

This course introduces students to relevant mathematical methods and their application in economics. A good understanding of these methods is crucial for students to comprehend important concepts in other selected areas in economics.

Course requirements

Assumed background

Students are expected to be familiar with algebra, calculus, and coordinate geometry.

Incompatible

You can't enrol in this course if you've already completed the following:

ECON1050

Course contact

School enquiries

Student Enquiries, School of Economics

All enquiries regarding student and academic administration (i.e. non-course content information, e.g., class allocation, timetables, extension to assessment due date, etc.) should be directed to enquiries@economics.uq.edu.au.

Enquiries relating specifically to course content should be directed to the Course Coordinator.

Course staff

Lecturer

Dr Kun Zhang

Tutor

Mr Ramazan Bora

Timetable

The timetable for this course is available on the UQ Public Timetable.

Additional timetable information

Workshops commence in Teaching Week 1.

Tutorials commence in Teaching Week 2.

Students are required to log their preferences for a tutorial group via My Timetable (available through my.UQ dashboard).

Important Dates:

  • Public Holidays: Wed 13 August (Royal Queensland Show Holiday), Mon 6 October (King’s Birthday public holiday).
  • Mid-Semester Break: 29 September – 3 October. Semester 2 classes recommence on Tue 7 October.

Students should refer to the timetable prior to the commencement of classes to ensure that they have the most up to date information, as from time to time late room changes may occur. 

Aims and outcomes

This course provides an introduction to the mathematical tools commonly used in economic analysis.

Learning outcomes

After successfully completing this course you should be able to:

LO1.

Represent and manipulate simple economic models algebraically.

LO2.

Use differential calculus, including partial derivatives and differentials, across a range of economic problems.

LO3.

Apply integration techniques to economic concepts such as consumer surplus and producer surplus.

LO4.

Apply methods of unconstrained and constrained optimization to simple economic problems.

LO5.

Use matrix algebra to solve sets of simultaneous equations and simple input-output models.

Assessment

Assessment summary

Category Assessment task Weight Due date
Project Assignment 1 30%

19/09/2025 - 26/09/2025

Assignment 1 will be released at 10 am on Friday, 19 September, and is due by 4 pm on Friday, 26 September.

Project Assignment 2 30%

24/10/2025 - 31/10/2025

Assignment 2 will be released at 10 am on Friday, 24 October, and is due by 4 pm on Friday, 31 October.

Examination Final Exam
  • Identity Verified
  • In-person
40%

End of Semester Exam Period

8/11/2025 - 22/11/2025

Assessment details

Assignment 1

Mode
Written
Category
Project
Weight
30%
Due date

19/09/2025 - 26/09/2025

Assignment 1 will be released at 10 am on Friday, 19 September, and is due by 4 pm on Friday, 26 September.

Learning outcomes
L01, L02, L04

Task description

The assignment will be a series of problems that test students' knowledge of the topics covered in workshops and tutorials. Assignment 1 will cover material from Topics 1 to 6.

This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.

A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.

To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.

Submission guidelines

Assignments must be hand written and legible. Scan the assignment (scanners are available at the Library) and create ONE pdf document. EXAMINE YOUR PDF DOCUMENT prior to submission to ensure it is legible and complete. Submit online through Blackboard Turnitin. More details will be provided on Blackboard.

Deferral or extension

You may be able to apply for an extension.

The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.

Extensions are limited to ensure timely feedback to other students.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

Assignment 2

Mode
Written
Category
Project
Weight
30%
Due date

24/10/2025 - 31/10/2025

Assignment 2 will be released at 10 am on Friday, 24 October, and is due by 4 pm on Friday, 31 October.

Learning outcomes
L02, L03, L04, L05

Task description

The assignment will be a series of problems that test students' knowledge of the topics covered in workshops and tutorials. Assignment 2 will cover material from Topics 3 to 10 (although this material is dependent on earlier topics as well).

This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.

A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.

To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.

Submission guidelines

Assignments must be hand written and legible. Scan the assignment (scanners are available at the Library) and create ONE pdf document. EXAMINE YOUR PDF DOCUMENT prior to submission to ensure it is legible and complete. Submit online through Blackboard Turnitin. More details will be provided on Blackboard.

Deferral or extension

You may be able to apply for an extension.

The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.

Extensions are limited to ensure timely feedback to other students.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

Final Exam

  • Identity Verified
  • In-person
Mode
Written
Category
Examination
Weight
40%
Due date

End of Semester Exam Period

8/11/2025 - 22/11/2025

Learning outcomes
L01, L02, L03, L04, L05

Task description

The exam will be two hours and will cover all topics from the course.

The final exam will be held during the examination period at a time and place set by Examinations Section. Important reminders and notices will be posted on Blackboard.

This assessment task is to be completed in-person. The use of generative Artificial Intelligence (AI) or Machine Translation (MT) tools will not be permitted. Any attempted use of AI or MT may constitute student misconduct under the Student Code of Conduct.

Exam details

Planning time 10 minutes
Duration 120 minutes
Calculator options

(In person) Casio FX82 series only or UQ approved and labelled calculator

Open/closed book Closed book examination - specified written materials permitted
Materials

One A4 sheet of handwritten or typed notes, single sided, is permitted

Exam platform Paper based
Invigilation

Invigilated in person

Submission guidelines

Deferral or extension

You may be able to defer this exam.

Course grading

Full criteria for each grade is available in the Assessment Procedure.

Grade Cut off Percent Description
1 (Low Fail) 0% - 29%

Absence of evidence of achievement of course learning outcomes.

2 (Fail) 30 - 46%

Minimal evidence of achievement of course learning outcomes.

3 (Marginal Fail) 47% - 49%

Demonstrated evidence of developing achievement of course learning outcomes

4 (Pass) 50% - 64%

Demonstrated evidence of functional achievement of course learning outcomes.

5 (Credit) 65% - 74%

Demonstrated evidence of proficient achievement of course learning outcomes.

6 (Distinction) 75% - 84%

Demonstrated evidence of advanced achievement of course learning outcomes.

7 (High Distinction) 85% - 100%

Demonstrated evidence of exceptional achievement of course learning outcomes.

Additional course grading information

A student’s final overall end-of-semester percentage mark will be rounded to determine their final grade. For example, 64.5% rounds to 65%, while 64.4% rounds to 64%.

Supplementary assessment

Supplementary assessment is available for this course.

Additional assessment information

Using AI at UQ

Visit the AI Student Hub for essential information on understanding and using Artificial Intelligence in your studies responsibly. 

Plagiarism

The School of Economics is committed to reducing the incidence of plagiarism. You are encouraged to read the UQ Student Integrity and Misconduct Policy available in the Policies and Procedures section of this course profile.

The Academic Integrity Module (AIM) outlines your obligations and responsibilities as a UQ student. It is compulsory for all new to UQ students to complete the AIM.

Learning resources

You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.

Library resources

Find the required and recommended resources for this course on the UQ Library website.

Learning activities

The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.

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Learning period Activity type Topic
Week 1

(28 Jul - 03 Aug)

Lecture

Lecture 1. Set Theory, Logic & Review of Algebra

Essentials of set theory and logic; real numbers; exponents; algebra; inequalities; intervals.

Learning outcomes: L01

Week 2

(04 Aug - 10 Aug)

Lecture

Lecture 2. Summation, Solving Equations

Summation notation; reviewing methods of solving equations.

Learning outcomes: L01

Tutorial

Tutorial 1

Set Theory, Logic & Review of Algebra

Learning outcomes: L01

Week 3

(11 Aug - 17 Aug)

Lecture

Lecture 3. Functions of One Variable

Linear functions; quadratic functions; polynomials; power, exponential and logarithmic functions; graphs of functions; inverse functions.

Learning outcomes: L01

Tutorial

Tutorial 2

Summation Notation & Solving Equations

Learning outcomes: L01

Week 4

(18 Aug - 24 Aug)

No student involvement (Breaks, information)

No Lecture or Tutorials

Week 5

(25 Aug - 31 Aug)

Lecture

Lecture 4. Calculus 1

Basic concepts; rules of differentiation.

Learning outcomes: L01, L02

Tutorial

Tutorial 3

Functions of One Variable

Learning outcomes: L01

Week 6

(01 Sep - 07 Sep)

Lecture

Lecture 5. Calculus 2

Derivatives in Use - Implicit differentiation; linear and polynomial approximations; Taylor's formula

Learning outcomes: L01, L02

Tutorial

Tutorial 4

Calculus 1

Learning outcomes: L01, L02

Week 7

(08 Sep - 14 Sep)

Lecture

Lecture 6. Calculus 3

Single-variable optimisation; determination of extreme points; local extreme points.

Learning outcomes: L01, L02, L04

Tutorial

Tutorial 5

Calculus 2

Learning outcomes: L01, L02

Week 8

(15 Sep - 21 Sep)

Lecture

Lecture 7. Calculus 4

Partial derivatives; multivariate optimisation.

Learning outcomes: L01, L02, L04

Tutorial

Tutorial 6

Calculus 3

Learning outcomes: L01, L02, L04

Week 9

(22 Sep - 28 Sep)

Lecture

Lecture 8. Calculus 5

Lagrange multiplier; introduction to constrained optimisation; applications.

Learning outcomes: L02, L04

Tutorial

Tutorial 7

Calculus 4

Learning outcomes: L01, L02, L04

Mid Sem break

(29 Sep - 05 Oct)

No student involvement (Breaks, information)

In-Semester Break

No workshop, no tutorials, and no consultations this week.

Week 10

(06 Oct - 12 Oct)

Lecture

Lecture 9. Calculus 6

Basic concepts of integration; indefinite and definite integrals; integration by parts; integration by substitution.

Learning outcomes: L01, L03

Tutorial

Tutorial 8

Calculus 5

Learning outcomes: L02, L04

Week 11

(13 Oct - 19 Oct)

Lecture

Lecture 10. Matrix Algebra 1 and 2

Introduction to linear algebra: matrix notation, matrix and vector operations.

Simultaneous equations, Gaussian elimination, determinants, minors and cofactors, Cramer's rule.

Learning outcomes: L01, L05

Tutorial

Tutorial 9

Calculus 6

Learning outcomes: L01, L03

Week 12

(20 Oct - 26 Oct)

Lecture

Lecture 11. Matrix Algebra 3

Cramer's rule; solving simultaneous equations; adjoint method for finding an inverse.

Learning outcomes: L01, L05

Tutorial

Tutorial 10

Matrix Algebra 1 & 2

Learning outcomes: L01, L05

Week 13

(27 Oct - 02 Nov)

Lecture

Lecture 12. Review

Exam preparation and a review of the course content.

Learning outcomes: L01, L02, L03, L04, L05

Tutorial

Tutorial 11

Matrix Algebra 3

Learning outcomes: L01, L05

Additional learning activity information

Make sure you check your student email and the ECON7150 Learn.UQ (Blackboard) site regularly (at least every few days). All important correspondence will be communicated to students via email or Learn.UQ throughout the semester.

UQ Extend

Before attending each weekly workshop, you must work through the relevant UQ Extent content (including videos and learning activities).

Workshops and Tutorials

It is essential that you attend the weekly workshops and tutorials to develop an in-depth understanding of mathematical techniques.

All tutorials in any week cover the same work and are based on material covered in the previous teaching week's workshop and UQ Extend content.

Consultation

Consultation is your chance to speak directly with the teaching staff. A timetable listing the consultation times and locations of teaching staff will be posted on the ECON7150 Learn.UQ site under Course Help. There is no need to make an appointment for a consultation, and you may attend any teaching staff's consultation session. However, note that consultation sessions may be busy before assessment due dates.

Do not hesitate to seek one-on-one help from teaching staff during consultation sessions. They are there to help. However, teaching staff will expect that you have performed your side of the bargain. If it becomes apparent that you are not dedicating an average of 10 hours per week to ECON7150, you will likely be asked to return to consultation only once you have done so.

Policies and procedures

University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:

Learn more about UQ policies on my.UQ and the Policy and Procedure Library.