Intended learning outcomes
- To recognize the matrix representation of multivariate data, knowing the multivariate normal distribution characteristics and applying the descriptive measures and the graphical representations on the multivariate data characterization.
- To apply methodologies that facilitate the understanding of the data, namely dimension reducing, and to identify its main features.
- To assess the need for the use of cluster analysis techniques and apply the methods of classification of objects in different groups according to a statistical distance function.
- To apply statistical methods of classification and determine functions of certain variables observed that enable to discriminate between these groups or classes.
- To apply multidimensional scaling (MDS) techniques. Use an MDS algorithm and interpret the graphical representation of the data.
- To implement multivariate methodologies through statistical software, in order to solve real problems.