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Multivariate Statistics (6544.4)

Level: Level 3 - Undergraduate Advanced Unit
Credit Points: 3
HECS Bands: 2, 4
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

    If a link to your Unit Outline is not displayed, please check back later. Unit Outlines are generally published by Week One of the relevant teaching period.

    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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