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STA8005 Multivariate Analysis for High-Dimensional Data

Units : 1
Faculty or Section : Faculty of Health, Engineering and Sciences
School or Department : School of Mathematics, Physics & Computing
Student contribution band : Band 1
Grading basis : Graded
Version produced : 17 May 2022


Pre-requisite or Co-requisite: STA8170 or STA2300 or STA1003


Statistics is concerned with the process of making sense out of data. It is the study of uncertainty and is concerned with the process of decision making in the face of uncertainty. As our ability to collect, accumulate and access data increases so does the Volume (amount), Variety (of types, sources and resolutions of data), Velocity (speed of data generation and handling) and Veracity (amount of noise and processing errors) of the data sets we wish to analyse and extract valuable information from. Variety creates wide or high-dimensional data sets that may require specific analytic approaches in order to distinguish useful patterns or develop predictive models for decision making.

This course covers some of the statistical concepts and methodologies appropriate for the analysis of large and/or high dimensional data sets. Students will learn the mathematical foundation of a number of statistical methods, the benefit and limitations of each method, how to correctly apply these methods using statistical software and how to assess the effectiveness of given analyses for given data sets. Students will also learn how to perform statistical analyses in the statistical software R. This will require students to master the writing of R code.

Course offers

Semester Mode Campus
Semester 1, 2022 Online
Date printed 17 May 2022