Multivariate Statistics (6544.4)
Level: | Level 3 - Undergraduate Advanced Unit |
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Credit Points: | 3 |
HECS Bands: | Band 1 2021 (Commenced After 1 Jan 2021) Band 1 2021 (Commenced Before 1 Jan 2021) Band 2 2013-2020 (Expires 31 Dec 2020) |
Faculty: | Faculty of Science and Technology |
Discipline: | Academic Program Area - Technology |
Availability
Unit Outlines
To view your Unit Outline, click View to log in to MyUC and access this information, or visit your unit's online teaching site.
- Semester 1, 2019, ON-CAMPUS, BRUCE (185230) - View
- Semester 1, 2018, ON-CAMPUS, BRUCE (181702) - View
- Semester 2, 2016, ON-CAMPUS, BRUCE (150623) - View
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Syllabus
This unit deals with multivariate statistical and data analytical methods for analysing multidimensional and big data. The practical background of analyses will be presented and computer packages will be used to carry out the analyses. Topics will be selected from descriptive statistics, data visualisation, descriptive data mining, regression and classification, predictive data mining, principal components analysis and other dimension reduction techniques. Applications to data and problems in business, natural and social sciences will be illustrated.
Learning Outcomes
On successful completion of this unit, students will be able to:
1. Describe the nature and properties of multivariate and big data;
2. Select and explain the appropriate statistical analysis for a given purpose and data set;
3. Evaluate the appropriateness and validity of a multivariate and analytic method; and
4. Produce and interpret the results by using a computer package.
Assessment Items
Contact Hours
A 2-hour lecture and a 2-hour lab per week.
Prerequisites
6540 Introduction to Statistics OR 5123 Business Statistics OR 1809 Data Analysis in Science
Corequisites
None.
Assumed Knowledge
None.
Incompatible Units
None.
Equivalent Units
None.
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