STAT315-12S2 (C)
Multivariate Statistical Methods
This is a semester two course worth 15 points.
Course Information
STAT315 and STAT463 are courses in multivariate statistical methods. Multivariate statistical methods extract information from datasets which consist of variables measured on a number of experimental units. Due to the large memory capacity available and with the advent of computing power, these methods are now widely applied in a variety of fields, including bioinformatics, epidemiology, finance and marketing. The course will cover the theory and application of various multivariate statistical methods, namely: multiple regression, principal component analysis, factor analysis, discriminant analysis, and clustering methods. It will also introduce the statistical analysis software SAS, which is a powerful tool when dealing with large multivariate datasets. R-syntax will also be briefly explained. Special attention will be given to practical applications and the interpretation of the results.
Learning outcomes
The courses will:
• introduce multiple and multivariate regression
• introduce principle component analysis (PCA) and factor analysis (FA)
• introduce discriminant analysis (DA) and clustering methods.
• introduce the use of statistical analysis software SAS
• give you experience in writing scientific and technical reports
You will be able to:
• choose appropriate method for analysis of your dataset
• use SAS procedures to perform the analysis
• be able to interpret the analysis results in such a way that a non-user of statistics can understand
• write a scientific and technical report.
Enquiries
Dr Elena Moltchanova
Room 600 Erskine Building
Phone Extension 6267