Notice
As part of Phase 3 of our return to campus plan, most units will now run tutorials, seminars and other small group learning activities on campus for the second half-year, while keeping an online version available for those students unable to return or those who choose to continue their studies online.
To check the availability of face to face activities for your unit, please go to timetable viewer. To check detailed information on unit assessments visit your unit's iLearn space or consult your unit convenor.
Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit Convenor/Lecturer
Nino Kordzakhia
Contact via By e-mail
Please refer to iLearn
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Credit points |
Credit points
10
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Prerequisites |
Prerequisites
STAT6170 or STAT670
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Corequisites |
Corequisites
STAT6180 or STAT680
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Co-badged status |
Co-badged status
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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:
See iLearn
Name | Weighting | Hurdle | Due |
---|---|---|---|
SGTA Works | 10% | No | Weeks 3, 5, 7 and 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: Weeks 3, 5, 7 and 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
Software:
SPSS and R
There are no prescribed texts for this unit, but the following list provides useful references.
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.
WEEK |
TOPICS |
WORK DUE |
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 |
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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 |
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