When undertaking research and critically judging the research of others with many variables, a key approach is use of multivariate data analysis. This online unit provides comprehensive skills essential for postgraduate students doing multivariate data analysis and for critically judging the research of others. We focus on the underlying principles you need to explore multivariate data sets and test hypotheses. In so doing, the unit provides you with an understanding of how multivariate research is designed, analysed and interpreted using statistics. The unit will cover the commonly used multivariate data analyses of principal components analysis, cluster analysis, discriminant functions analysis and non-metric multidimensional scaling, as well as parametric and permutational hypothesis testing techniques. Examples of data will be cross-disciplinary, enabling students from many disciplines to appreciate the techniques. Analyses will use the R statistical environment, furthering student skills in this programming environment. By doing this unit, you will be able to use multivariate data analyses using a wide-range of data and present in a format for publication.
online lecture and practical material, 4 hours face-to-face classes
2 x online quizzes (12.5% each, total 25%), 2 x online quizzes (15% each, total 30%), 'methods and results' report (45%)