Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit Convenor
Karol Binkowski
Unit Convenor
Jun Ma
Jun Ma
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Credit points |
Credit points
10
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Prerequisites |
Prerequisites
|
Corequisites |
Corequisites
|
Co-badged status |
Co-badged status
STAX1170
STAT6170
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Unit description |
Unit description
This unit provides a broad introduction to statistical concepts and data analysis techniques, providing basic statistical knowledge. The unit dedicates itself to developing an understanding of statistical practice and illustrates this by studying the techniques most commonly employed in the sciences, social sciences, and humanities. Topics covered in this unit include data collection methods, data quality, data summarisation, basic probability, random variables, and statistical models like the normal distribution, followed by sampling distributions and statistical inferences about means and proportions. Also studied are analysis methods relating to comparisons, counted data and relationships, including regression and correlation. Excel is used for handling and analysing data and word processing to report the results. |
Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
On successful completion of this unit, you will be able to:
Requirements to Pass this Unit: To pass this unit, you must:
Participation in learning activities:
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 enhances your learning experience and contributes to a vibrant and dynamic learning environment for everyone.
Classes:
Weekly class participation is expected throughout the session. Students are expected to attend all classes and participate in activities. Participation in all classes will enhance your chances of success in the unit, as these are where we engage with the unit material via active learning and prepare and revise for other unit assessments.
Late Assessment Submission Penalty:
Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark) will be applied each day a written assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of 0 will be awarded even if the assessment is submitted. Submission time for all written assessments is set at 11:55 pm. A 1-hour grace period is provided to students who experience a technical concern. For any late submission of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, students need to submit an application for Special Consideration.
Assessments where Late Submissions will be accepted.
Special Considerations:
The Special Consideration Policy aims to support students impacted by short-term circumstances or events that are serious, unavoidable, and significantly disruptive and 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/s/.
Name | Weighting | Hurdle | Due |
---|---|---|---|
Generative AI Research Poster | 30% | No | Week 4 |
Excel based practical test in class | 40% | No | Week 9 |
Module Test | 30% | No | Week 13 |
Assessment Type 1: Case study/analysis
Indicative Time on Task 2: 7 hours
Due: Week 4
Weighting: 30%
Students analyze a dataset and create a research poster summarizing their findings, using AI tools to assist with components like data visualization, summaries, or layout suggestions. The submission includes the poster and a reflection on how AI was used ethically, what aspects they improved manually, and the importance of human oversight in academic work. Assessment Focus: Data communication, creativity, and ethical AI use.
Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 1 hours
Due: Week 9
Weighting: 40%
During the in-class Excel-based invigilated test, students will demonstrate their practical knowledge by applying statistical techniques to a given dataset.
Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 2 hours
Due: Week 13
Weighting: 30%
This unit is structured into multiple modules, with a test designed to assess the content of modules. This particular assessment is non-invigilated.
1 If you need help with your assignment, please contact:
2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation
The statistics content will be delivered in classes from Week 1 to Week 13 (except Week 9 where the test takes place in Practical classes). Specifically, students should work through the following material every week:
We will communicate with you via your university email or through announcements on iLearn. You can also post queries to convenors on the iLearn discussion board or send them to your lecturers [or stat1170.admin@mq.edu.au] from your university email address.
For the latest information on the University’s response to COVID-19, please refer to the Coronavirus infection page on the Macquarie website: https://www.mq.edu.au/about/coronavirus-faqs.
Please check this page regularly for information and changes in requirements during the semester. If this unit regarding COVID-19 changes, we will communicate these via iLearn.
Assistance
For help with any matters related to this unit, students should contact the appropriate department staff by emailing stat1170.admin@mq.edu.au.
Recommended textbook for this unit:
Other recommended reading:
iLearn (a version of Moodle) is used to deliver course material and can be accessed at http://ilearn.mq.edu.au.
The Don McNeil Prize for Introductory Statistics is named in honour of the foundation Professor of Statistics at Macquarie University. The prize is awarded twice per year to the student with the best overall performance in a first-year statistics unit.
Week | Lecture Topic | Assessment due |
1 | Data; research questions; graphics | |
2 | Random Variables; Binomial distribution | |
3 | Normal distribution | |
4 | Sampling distributions | GenAI Research Poster |
5 | Hypothesis tests for population mean | |
6 | Comparing population means | |
7 | Power of a hypothesis test | |
8 | Simple linear regression | |
9 | Significance of regression | Module 1, 2 & 3 Excel Practical Test invigilated |
10 | Advanced regression | |
11 | Categorical data analysis | |
12 | Categorical data analysis | |
13 | No lecture | Module 4 & 5 online quiz |
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.
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 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
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.
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
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.
Macquarie University offers a range of Student Support Services including:
Got a question? Ask us via the Service Connect Portal, or contact Service Connect.
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.
The Employability module has been removed from the unit. Instead, new topics have been introduced in Week 2, Week 7, and Week 10 (refer to the unit schedule). Additionally, Module Tests have been replaced by three assessments (refer to the assessment tasks section of the unit guide).
Unit information based on version 2025.05 of the Handbook