Applied Statistical Computing and Multivariate Methods ((4))

Catalog description

This course introduces graduate students to common applied multivariate statistical methods, topics in data management, and interactive data visualization. Use of the R programming language to motivate understanding of a wide variety of issues related to data management and the analysis of complex datasets and programming with data. Essential programming concepts include data processing tasks, data manipulation, conditional execution, and other data management fundamentals. Statistical analyses cover high-dimensional data visualization, principal component analysis, and factor analysis. For visualization, interactive data-driven dashboards with R Shiny will be created, integrating visualizations and user interfaces to enable real-time exploration and storytelling. Emphasis may be placed on applications to areas relevant to the graduate students' field of study.