Cognitive: Programming techniques in statistical programming language (R) in combination with advanced statistical methodologies. Particular emphasis on the construction of appropriate statistical models to describe complex relationships.
Skills: The student learns to use an advanced statistical language in order to be able to interpret data analysis results but also to construct models that explain relationships and are used in predictions.
Course Content (Syllabus)
Statistical programming techniques with R. Data structures for statistical analysis. Description and visualization of multivariate data. Hypotheses tests and multivariate methodologies focusing on algorithmic techniques for distribution estimation, random number generation, confidence intervals and hypothesis tests with resampling, non parametric regression, etc.