Course coordinator
Dr Kun Zhang
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
|
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 |
| 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.
Filter activity type by
Please select
| 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:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments for Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.