Students

STAT3110 – Statistical Inference

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
Jun Han
Contact via email
See iLearn for consultation hours.
Credit points Credit points
10
Prerequisites Prerequisites
20cp at 2000 level including (STAT2372 or STAT2173) or (STAT2170 and COMP2200)
Corequisites Corequisites
Co-badged status Co-badged status
STAT6110
Unit description Unit description

While numerous advanced data algorithms are readily available for  efficient data analysis, it remains crucial to understand the internal workflows of these 'black boxes.' A robust data analysis workflow hinges on a profound understanding of statistical inference and the capacity to critically assess and compare different statistical procedures. This unit equips you with the essential tools required to construct optimal methods for estimation and hypothesis testing, empowering you to employ the most suitable statistical analyses across a wide spectrum of scenarios. Complementing the theory, this unit incorporates simulation-based exercises, facilitating the development of an intuitive grasp of statistical inference. An introduction to Bayesian inference principles is also provided. 

Learning in this unit enhances student understanding of global challenges identified by the United Nations Sustainable Development Goals (UNSDGs) Industry, Innovation and Infrastructure

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: Apply random sampling concepts and estimation principles to assess the performance of inference procedures.  
  • ULO2: Analyse a range of statistical inference contexts, including frequentists and Bayesian methods, and employ the concept and principles of likelihood.
  • ULO3: Use hypothesis testing approaches to carry out statistical tests in various contexts. 
  • ULO4: Design and apply simulation-based inference to various statistical inference procedures
  • ULO5: Effectively communicate statistical inference procedures and results to diverse audiences. 

General Assessment Information

Attendance and participation

We strongly encourage all students to participate actively in all learning activities. Regular engagement is crucial for your success in this unit, as these activities provide opportunities to deepen your understanding of the material, collaborate with peers, and receive valuable feedback from instructors, to assist in completing the unit assessments. Your active participation not only enhances your own learning experience but also contributes to a vibrant and dynamic learning environment for everyone.

Requirements to Pass this Unit

To pass this unit, you must:

  • Achieve a total mark equal to or greater than 50%.

Hurdle Assessments

There is no Hurdle Assessment in this unit.

Late Submission Policy

  • 5% penalty per day: If you submit your assessment late, 5% of the total possible marks will be deducted for each day (including weekends), up to 7 days.

    • 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 1 day late, you will lose 1.5 marks and receive 25.5/30.

  • After 7 days: Submissions more than 7 days late will receive a mark of 0.

  • 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 HERE.

Assessments where Late Submissions will be accepted:

  • Assignments – YES, Standard Late Penalty applies;
  • Final Exam – NO, unless Special Consideration is granted.

Special Consideration

The Special Consideration Policy aims to support students who have been impacted by short-term circumstances or events that are serious, unavoidable, and significantly disruptive, and which may affect their performance in assessment. If you experience circumstances or events that affect your ability to complete the assessments in this unit on time, please inform the convenor and submit a Special Consideration request through https://connect.mq.edu.au.

Written Assessments/Quizzes/Tests: If you experience circumstances or events that affect your ability to complete the written assessments in this unit on time, please inform the convenor and submit a Special Consideration request through https://connect.mq.edu.au.

Assessment Tasks

Name Weighting Hurdle Due Groupwork/Individual Short Extension AI assisted?
Assignment 25% No 20/03/2026 Individual No Open AI
Assignment 25% No 15/05/2026 Individual No Open AI
Final Exam 50% No Exam Period Individual No Observed

Assignment

Assessment Type 1: Problem-based task
Indicative Time on Task 2: 12 hours
Due: 20/03/2026
Weighting: 25%
Groupwork/Individual: Individual
Short extension 3: No
AI assisted?: Open

Reinforce and apply the concepts and skills learned in the unit through data analysis.


On successful completion you will be able to:
  • Apply random sampling concepts and estimation principles to assess the performance of inference procedures.  
  • Analyse a range of statistical inference contexts, including frequentists and Bayesian methods, and employ the concept and principles of likelihood.
  • Design and apply simulation-based inference to various statistical inference procedures

Assignment

Assessment Type 1: Problem-based task
Indicative Time on Task 2: 12 hours
Due: 15/05/2026
Weighting: 25%
Groupwork/Individual: Individual
Short extension 3: No
AI assisted?: Open

Use the statistical testing and inference concepts in the simulated scenarios.


On successful completion you will be able to:
  • Apply random sampling concepts and estimation principles to assess the performance of inference procedures.  
  • Analyse a range of statistical inference contexts, including frequentists and Bayesian methods, and employ the concept and principles of likelihood.
  • Use hypothesis testing approaches to carry out statistical tests in various contexts. 
  • Design and apply simulation-based inference to various statistical inference procedures
  • Effectively communicate statistical inference procedures and results to diverse audiences. 

Final Exam

Assessment Type 1: Examination
Indicative Time on Task 2: 18 hours
Due: Exam Period
Weighting: 50%
Groupwork/Individual: Individual
Short extension 3: No
AI assisted?: Observed

Formal invigilated examination testing the learning outcomes of the unit.


On successful completion you will be able to:
  • Apply random sampling concepts and estimation principles to assess the performance of inference procedures.  
  • Analyse a range of statistical inference contexts, including frequentists and Bayesian methods, and employ the concept and principles of likelihood.
  • Use hypothesis testing approaches to carry out statistical tests in various contexts. 

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

Classes

Workshops (beginning in Week 1): There is one 1-hour workshop each week. During this hour, we will provide a brief overview of the week's content, run a Q&A session, and engage in some interesting activities together. 

Pre-recorded Lectures (released weekly from Week 1): There are no formal live lectures scheduled for this unit. Each week, we will have some video recordings covering the unit materials.

SGTA classes (beginning in Week 2): Students must register for and attend one 2-hour class per week.

The timetable for classes can be found on the University website at: https://publish.mq.edu.au

Enrolment can be managed using eStudent at: https://students.mq.edu.au/support/technology/systems/estudent

Technology Used and Required

This subject requires the use of the following computer software:

  • R: R is a free statistical software package. Access and installation instructions may be found at: https://www.r-project.org/
  • RStudio: RStudio is an open-source tool that is used to manage and present work performed using R. Access and installation instructions may be found at https://rstudio.com/products/rstudio/download/
  • LaTeX: LaTeX is a free mathematical typesetting program. Access and installation instructions may be found at: https://www.latex-project.org/get/
  • Quarto: An open-source scientific and technical publishing system, installed by default with the latest release of RStudio. 

Students are invited to bring their own devices (BYOD), and a laptop is recommended. Acceptable platforms are Windows, Linux and Mac. 

Suggested textbooks

The following textbook is useful as a supplementary resource, for additional questions and explanations. They are available from the Macquarie University library:

  • Wackerly, D.,  W. Mendenhall, and R. L. Scheaffer, Mathematical Statistics with Applications. Thomson Brooks/Cole, 7th edition, 2008.

Communication

We will communicate with you via your university email or through announcements on iLearn. Queries to convenors can either be placed on the iLearn discussion forum or sent to your lecturers from your university email address.

Unit Schedule

Week Topic
1 Probability and random samples
2 - 3 Large sample probability concepts
4 Estimation concepts
5 - 6 Likelihood
Session 1 Break  
7 - 8 Estimation methods
8 - 9 Hypothesis testing concepts
10 - 11 Hypothesis testing methods
12 Bayesian inference
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 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.

Changes from Previous Offering

We value student feedback to be able to continually improve the way we offer our units. As such, we encourage students to provide constructive feedback via student surveys, to the teaching staff directly, or via the FSE Student Experience & Feedback link in the iLearn page.

Student feedback from the previous offering of this unit was very positive overall, with students pleased with the clarity around assessment requirements and the level of support from teaching staff. As such, no change to the delivery of the unit is planned; however, we will continue to strive to improve the level of support and student engagement.


Unit information based on version 2026.02 of the Handbook