Multivariate Statistics G (6555.4)
|HECS Bands:||2, 4|
|Faculty:||Faculty of Science and Technology|
|Discipline:||Academic Program Area - Technology|
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- Semester 1, 2019, ON-CAMPUS, BRUCE (185240) - View
- Semester 1, 2018, ON-CAMPUS, BRUCE (181723) - View
- Semester 2, 2016, ON-CAMPUS, BRUCE (151470) - View
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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.
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;
4. Interpret the results established by using a computer package;
5. Produce the results of analyses in a form which is suitable for publication; and
6. Explain the characteristics of data visualisation methods.
A 2-hour lecture and a 2-hour lab per week
6275 Statistical Analysis and Decision Making G OR 6554 Introduction to Statistics G OR 1809 Data Analysis in Science