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Unit of study_
OLET5610: Multivariate Data Analysis
2023 unit information
When undertaking research and critically judging the research of others with many variables, a key approach is use of multivariate data analysis. This online unit provides comprehensive skills essential for postgraduate students doing multivariate data analysis and for critically judging the research of others. We focus on the underlying principles you need to explore multivariate data sets and test hypotheses. In so doing, the unit provides you with an understanding of how multivariate research is designed, analysed and interpreted using statistics. The unit will cover the commonly used multivariate data analyses of principal components analysis, cluster analysis, discriminant functions analysis and non-metric multidimensional scaling, as well as parametric and permutational hypothesis testing techniques. Examples of data will be cross-disciplinary, enabling students from many disciplines to appreciate the techniques. Analyses will use the R statistical environment, furthering student skills in this programming environment. By doing this unit, you will be able to use multivariate data analyses using a wide-range of data and present in a format for publication.
Unit details and rules
Managing faculty or University school:
Life and Environmental Sciences Academic Operations
| Code | OLET5610 |
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| Academic unit | Life and Environmental Sciences Academic Operations |
| Credit points | 2 |
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Prerequisites:
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None |
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Corequisites:
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None |
| Prohibitions:
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None |
At the completion of this unit, you should be able to:
- LO1. demonstrate a key understanding of multivariate data, it limitations and uses
- LO2. design studies with multivariate data
- LO3. use a number of ordination methods with statistical tests for multivariate data
- LO4. able to perform multivariate analyses within the R statistical environment
- LO5. able to present multivariate analysis graphs for publication
Unit availability
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The outline is published 2 weeks before the first day of teaching. You can look at previous outlines for a guide to the details of a unit.
Modes of attendance (MoA)
This refers to the Mode of attendance (MoA) for the unit as it appears when you’re selecting your units in Sydney Student. Find more information about modes of attendance on our website.
