Multivariate Statistics (SL_119)
About Study Course
Objective
The aim of the course is to introduce the tools and concepts of multivariate data analysis with a strong focus on applications with R program.
Prerequisites
Higher mathematics, probability, statistics, linear models, basic knowledge of R programming.
Learning outcomes
Student:
• has gained an in-depth knowledge of the theoretic probabilistic concepts related to multivariate analysis.
• illustrates the visualization techniques describing the multivariate data.
• assesses the most important multivariate techniques such as principal components analysis, factor analysis, cluster analysis and discriminant analysis.
• Implements appropriate multivariate data visualizations in R programme.
• Can independently apply multivariate data analysis techniques in R programme, to carry out research activities or highly qualified professional functions.
• Can compare and understand the aims of various multivariate data analysis methods and choose the most appropriate for the analysis of the data set.
• Can generate hypothesis and make analysis-based decisions related to multivariate data.
Study course planning
| Study programme | Study semester | Program level | Study course category | Lecturers | Schedule |
|---|---|---|---|---|---|
| Biostatistics, MFBS | 3 | Master’s | Required | Māris Munkevics |
