Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit Convenor
Karol Binkowski
Contact via karol.binkowski@mq.edu.au
12WW, room 614
Refer to iLearn page
Unit Convenor
Connor Smith
Contact via connor.smith@mq.edu.au
12WW, room 617
Refer to iLearn page
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Credit points |
Credit points
10
|
Prerequisites |
Prerequisites
STAT6170 or STAT670
|
Corequisites |
Corequisites
STAT6180 or STAT680
|
Co-badged status |
Co-badged status
STAT3102
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Unit description |
Unit description
This unit introduces statistical tools for multivariate data analysis such as statistical graphics, discriminant analysis, principal component analysis, cluster analysis and an introduction to data mining, especially classification. Statistical packages are used extensively to illustrate the concepts. |
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:
All assignments are individual assessment tasks. There is no group work. More details will be provided on the iLearn page in due course.
HURDLE ASSESSMENTS
There is no hurdle assessment.
LATE SUBMISSION OF WORK
Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark of the task) will be applied for each day a written report or presentation 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. The submission time for all uploaded assessments is 11:55 pm. A 1-hour grace period will be 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, please apply for Special Consideration.
Assessments where Late Submissions will be accepted
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 ask.mq.edu.au.
ASSIGNMENT SUBMISSION
Assignment submission will be online through the iLearn page. Read the submission statement carefully before accepting it as there are substantial penalties for making a false declaration. It is your responsibility to make sure your assignment submission is legible. If there are technical obstructions to your submission online, please email us to let us know. You may submit as often as required prior to the due date/time. Please note that each submission will completely replace any previous submissions. It is in your interests to make frequent submissions of your partially completed work as insurance against technical or other problems near the submission deadline.
Name | Weighting | Hurdle | Due |
---|---|---|---|
SGTA Works | 10% | No | Week 3; 5; 7; 10 |
Mid-Semester test | 30% | No | Week 8 |
Practical Test | 60% | No | Week 12 |
Assessment Type 1: Qualitative analysis task
Indicative Time on Task 2: 40 hours
Due: Week 3; 5; 7; 10
Weighting: 10%
The tasks given during four SGTA computer lab sessions are to be completed within the allocated time and submitted via iLearn. The four SGTA Works are worth 10% in total.
Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 1 hours
Due: Week 8
Weighting: 30%
Further information for this online test will be provided in the iLearn site of the unit.
Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 2 hours
Due: Week 12
Weighting: 60%
This is an open book style online exam. The practical test is designed to examine the use of software for data analysis and the software output interpretation skills taught in the unit.
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
Classes
Lectures (beginning in Week 1): There is one one-hour face to face lecture each week and two-hours of pre-recorded material.
SGTA classes (beginning in Week 2): Students must register in and attend one two-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
Suggested Textbooks
The following books are highly recommended reading materials.
Chambers J M et al (1983) Graphical Methods for Data Analysis;
Cleveland W S (1994) Elements of Graphing Data;
Tufte E R (2001) The Visual Display of Quantitative Information;
Everitt B S et al (2001) Applied multivariate data analysis;
Johnson, R.A. & Wichern, D.W. (2002) Applied Multivariate Statistical Analysis;
Manly, B F J (2004) Multivariate Statistical Methods - A Primer.
Technology Used and Required
This subject requires the use of the following computer software:
Communication
We will communicate with you via your university email, iLearn forums, or through announcements on iLearn. Queries to the convenors can either be placed on the iLearn discussion board or sent to the staff email address from your university email address.
COVID Information
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. Remember to check this page regularly in case the information and requirements change during semester. If there are any changes to this unit in relation to COVID, these will be communicated via iLearn.
Week |
Topic |
Due |
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1 |
Introduction |
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2 |
Different graphical displays |
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3 |
Displaying multivariate data |
SGTA Work |
4 |
Similarities and distances |
|
5 |
Hierarchical cluster analysis |
SGTA Work |
6 |
K-means clustering |
|
7 |
Eigenvalues and eigenvectors |
SGTA Work |
8 |
Principal component analysis |
Mid-Semester Test |
9 |
Principal component analysis cont. |
|
10 |
Discriminant analysis |
SGTA Work |
11 |
Classification Trees Revision |
|
12 |
Final assessment: |
Practical Test |
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 ask.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/
The Writing Centre 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 AskMQ, 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.
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 the level of student engagement
Unit information based on version 2024.01R of the Handbook