Course coordinator
Dr Temesgen Kifle
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
Statistical inference, probability & sampling distributions, estimation, hypothesis tests, correlation & regression, experimental design, sample survey design, quality sampling, modern business decision theory.
ECON7300 is a postgraduate course in introductory statistics designed primarily for Business, Commerce and Economics students. The course covers a variety of statistical concepts and techniques applicable to the collection, presentation, interpretation and use of numerical data, including probability and sampling distributions, hypothesis testing, analysis of variance, simple and multiple linear regression, time-series forecasting, and decision analysis. It provides the foundation for understanding statistical procedures that help students do solid statistical analysis in business and economic situations.
The course includes access to learning content on the UQ Extend platform, with studio-produced video segments and accompanying learning activities. Students must work through the relevant UQ Extend course content and complete a pre-lecture quiz before each scheduled lecture. Lectures will focus on the more complex concepts and practical statistical applications, providing students with additional learning opportunities in class.
Course requirements
Assumed background
This course is a basic Statistics Course. Accordingly, not having any background in Statistics will not have any bearing on your performance in this course.ﾠ
As forﾠany math-related course, performance and success of a studentﾠgreatlyﾠdepends on the amount of work, persistence and diligence in studying all the materialﾠfrom the lectures, workshops, tutorials, completinigﾠassignments and tests that the student invests in during the study period.
Before attempting this course, you are advised that it is important to complete the appropriate prerequisite course(s) listed on the from of the course profile. No responsibility will be accepted by UQ School of Economics, the Faculty of Business, Economics and Law or The University of Queensland for poor student performance occurring in courses where the appropriate prerequisites(s) has/have not been completed, for any reason whatsoever.
Recommended prerequisites
We recommend completing the following courses before enrolling in this one:
Snr Maths I or B or MATH1040 or MP127 or MT140 or equiv.
Incompatible
You can't enrol in this course if you've already completed the following:
ECON1310
Course contact
School enquiries
School 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.ﾠ
Enquiries relating specifically to course content should be directed to the Course Coordinator/Lecturer at econ7300@uq.edu.au.
Course staff
Lecturer
Dr Temesgen Kifle
Tutor
Dr Temesgen Kifle
Mrs Eugenia Arrarte Brown
Mr Reuben Horne
Miss Milagros Victoria Aguilar Palpa
Ms Josephine Tai
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
Workshops (scheduled lectures) commence in Week 1.
Tutorials commence in Week 2.
Consultations commence in 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: Wednesday 13 August (Royal Queensland Show Holiday, EKKA), Monday 6 October (King's Birthday)
- In-Semester Break: 29 September - 3 October. Semester 1 classes recommence on Mon 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
ﾠ As a postgraduateﾠcourse, ECON7300 introduces key procedures for measuring and analysing economic and business variables.ﾠThis course is designed to provide a solid understanding of quantitative concepts used in economics and business. We live and work in an uncertain world. We take risks on all sorts of things daily: weather, markets, traffic, investments, casinos and so on. Businesses and governments operate with similar uncertainties. Information costs could be quite high, and we can never measure everything. Inevitably, important decisions must be made based on a limited set of information. Training in statistics will help you to make more informed and better decisions for the future.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Quiz |
Pre-lecture Quizzes
|
20% (best 8 of 11) |
Pre-lecture Quiz 1: O-week Tue - Week 1 Mon Pre-lecture Quiz 2: Week 1 Tue - Week 2 Mon Pre-lecture Quiz 3: Week 2 Tue - Week 3 Mon Pre-lecture Quiz 4: Week 3 Tue - Week 4 Mon Pre-lecture Quiz 5: Week 4 Tue - Week 5 Mon Pre-lecture Quiz 6: Week 5 Tue - Week 6 Mon Pre-lecture Quiz 7: Week 6 Tue - Week 7 Mon Pre-lecture Quiz 8: Week 7 Tue - Week 8 Mon Pre-lecture Quiz 9: Week 8 Tue - Week 9 Mon Pre-lecture Quiz 10: Week 10 Tue - Week 11 Mon Pre-lecture Quiz 11: Week 11 Tue - Week 12 Mon
Pre-lecture quizzes are due by 4:00 pm on the relevant Mondays. |
| Project |
Project
|
30% |
14/10/2025 4:00 pm |
| Examination |
End-of-semester Exam
|
50% |
End of Semester Exam Period 8/11/2025 - 22/11/2025 |
Assessment details
Pre-lecture Quizzes
- Online
- Mode
- Written
- Category
- Quiz
- Weight
- 20% (best 8 of 11)
- Due date
Pre-lecture Quiz 1: O-week Tue - Week 1 Mon
Pre-lecture Quiz 2: Week 1 Tue - Week 2 Mon
Pre-lecture Quiz 3: Week 2 Tue - Week 3 Mon
Pre-lecture Quiz 4: Week 3 Tue - Week 4 Mon
Pre-lecture Quiz 5: Week 4 Tue - Week 5 Mon
Pre-lecture Quiz 6: Week 5 Tue - Week 6 Mon
Pre-lecture Quiz 7: Week 6 Tue - Week 7 Mon
Pre-lecture Quiz 8: Week 7 Tue - Week 8 Mon
Pre-lecture Quiz 9: Week 8 Tue - Week 9 Mon
Pre-lecture Quiz 10: Week 10 Tue - Week 11 Mon
Pre-lecture Quiz 11: Week 11 Tue - Week 12 Mon
Pre-lecture quizzes are due by 4:00 pm on the relevant Mondays.
Task description
Each of the 11 Pre-lecture Quizzes is worth 2.5%, and only the best 8 of 11 will count towards the assessment mark.
Each Monday, starting in Orientation Week, studio and pen videos for the next week's topic will become available on UQ Extend. Students need to watch the relevant studio and pen videos on UQ Extend before completing the pre-lecture quiz between Tuesday at 4:00 pm and Monday at 4:00 pm of the following week.
For instance, Topic 1 will become available on UQ Extend on the Monday of the Orientation Week. Students are expected to complete Pre-lecture Quiz 1 between 4:00 pm on the Tuesday in the Orientation Week and 4:00 pm on the Monday in Week 1. Students need to watch the pen and studio videos related to Topic 1 on UQ Extend before completing Pre-lecture Quiz 1.
Online test marking is automated, and the best out of two attempts for each quiz will contribute towards the aggregate quiz result. All the pre-lecture quizzes contain questions requiring calculation. Please follow the instructions given in each question regarding the rounding to decimal places.
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
The pre-lecture quizzes must be completed and submitted electronically by the due date and time through the relevant assessment submission link, located in the Assessment > Pre-lecture Quizzes section of the course Learn.UQ (Blackboard) site.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
As the best 8 out of 11 pre-lecture quizzes count towards this assessment, there is no extension or deferral.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
Project
- Online
- Mode
- Written
- Category
- Project
- Weight
- 30%
- Due date
14/10/2025 4:00 pm
Task description
The Project will require students to complete and submit an individual practical assignment covering Topics 6 to 9 (inclusive). Full details of the requirements for the project will be posted on the course Learn.UQ (Blackboard) site.
Mark(s) for the assignment will be awarded for selection of appropriate methods/formulas, computation of correct numerical answers, and interpretation of results.
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
The project must be submitted electronically by the due date and time through the relevant assessment submission link, located in the Assessment > Project section of the course Learn.UQ (Blackboard) site. Email submissions will not be accepted.
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 7 calendar days 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.
End-of-semester Exam
- Identity Verified
- In-person
- Mode
- Written
- Category
- Examination
- Weight
- 50%
- Due date
End of Semester Exam Period
8/11/2025 - 22/11/2025
- Other conditions
- Time limited.
Task description
The End-of-Semester Exam will be an on-campus, invigilated, closed-book (specified written materials permitted) exam covering Topics 1 to 5 and 10 to 12 (inclusive). The questions will be a mix of multiple-choice (MCQs), short answers, and problem-solving.
The exam will be centrally timetabled, scheduled during the end-of-semester examination period at a time and date to be confirmed.
You will be alerted to further information about the End-of-Semester Exam on the course Learn.UQ (Blackboard) site.
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 | Unmarked bilingual dictionary |
| 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.
Additional learning resources information
All course content, including lecture slides and tutorial materials, will be made available to students through Learn.UQ (Blackboard). The Learn.UQ site further provides access to UQ Extend, a learning platform where studio-produced content videos, slide handouts, and other learning materials can be accessed.
Note: Lecture slides are not a substitute for the learning content on UQ Extend and the required readings specified in this course profile. Instead, lectures provide additional learning opportunities with lecture slides being a supplemental learning guide.
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 |
Topic 1 Basic Probability |
Week 2 (04 Aug - 10 Aug) |
Tutorial |
Tutorial 1 Basic Probability |
Lecture |
Topic 2 Probability Distributions |
|
Week 3 (11 Aug - 17 Aug) |
Tutorial |
Tutorial 2 Probability Distributions Wednesday 13/08/2025 EKKA Public Holiday No tutorials on this day. Students are invited to attend another tutorial for this week only. |
Lecture |
Topic 3 Sampling Distributions & Confidence Interval Estimation |
|
Week 4 (18 Aug - 24 Aug) |
Tutorial |
Tutorial 3 Sampling Distributions & Confidence Interval Estimation |
Lecture |
Topic 4 Hypothesis Testing: One-sample Tests |
|
Week 5 (25 Aug - 31 Aug) |
Tutorial |
Tutorial 4 Hypothesis Testing: One-sample Tests |
Lecture |
Topic 5 Hypothesis Testing: Two-sample Tests |
|
Week 6 (01 Sep - 07 Sep) |
Tutorial |
Tutorial 5 Hypothesis Testing: Two-sample Tests |
Lecture |
Topic 6 Analysis of Variance (ANOVA) |
|
Week 7 (08 Sep - 14 Sep) |
Tutorial |
Tutorial 6 Analysis of Variance (ANOVA) |
Lecture |
Topic 7 Simple Linear Regression |
|
Week 8 (15 Sep - 21 Sep) |
Tutorial |
Tutorial 7 Simple Linear Regression |
Lecture |
Topic 8 Multiple Linear Regression I |
|
Week 9 (22 Sep - 28 Sep) |
Tutorial |
Tutorial 8 Multiple Linear Regression I |
Lecture |
Topic 9 Multiple Linear Regression II |
|
Mid Sem break (29 Sep - 05 Oct) |
No student involvement (Breaks, information) |
Mid-Semester Break No lecture, no tutorials, no consultations |
Week 10 (06 Oct - 12 Oct) |
Tutorial |
Tutorial 9 Multiple Linear Regression II Monday 06/10/2025 King's Birthday Public Holiday No tutorials on this day. Students are invited to attend another tutorial for this week only. |
Lecture |
Topic 10 Time-series Forecasting I |
|
Week 11 (13 Oct - 19 Oct) |
Lecture |
Topic 11 Time-series Forecasting II & Index Numbers |
Tutorial |
Tutorial 10 Time-series Forecasting I |
|
Week 12 (20 Oct - 26 Oct) |
Lecture |
Topic 12 Chi-Square Test & Decision Analysis |
Tutorial |
Tutorial 11 Time-series Forecasting II & Index Numbers |
|
Week 13 (27 Oct - 02 Nov) |
Lecture |
Revision |
Tutorial |
Tutorial 12 Chi-Square Test & Decision Analysis |
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.