Statistical Learning with Applications in R

Education facts

Code: STGC22

Content Students acquire knowledge of modern methods of statistical learning. Supervised methods of learning: \- regression methods \- classification methods \- support vector machine Unsupervised methods of learning: \- principal component analysis \- k-means clustering and hierarchical clustering R commands

Entry requirements

Prerequisites 60 ECTS credits completed in Statistics

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• Statistical Learning with Applications in R

  Karlstad University

  Karlstad

  Start date: 18 January 2027

  End date: 28 March 2027

  Pace of study: 50 %