MA3405 - Multivariate Statistical Methods

Credit points:	03
Year:	2013
Student Contribution Band:	Band 2
Administered by:	School of Engineering

Multivariate descriptive statistics, linear models and MANOVA, principal components, correspondence, factor, discriminant, canonical correlation and cluster analysis. Use of packaged statistics software.

Learning Outcomes

• to give the student a firm understanding of statistical methods, essential for extracting information from multivariate and "real world" data.

Prerequisites:

MA2405

Availabilities
Townsville, Internal, Study Period 2
Census Date 29-Aug-2013
Coord/Lect:	Dr Yvette Everingham.
Contact hours:	26 hours lectures 13 hours practicals
Assessment:	end of semester exam (70%); other exams (10%); assignments (20%).

Note: Minor variations might occur due to the continuous Subject quality improvement process, and in case of minor variation(s) in assessment details, the Subject Outline represents the latest official information.