Statistics: High-dimensional Data Analysis

Education facts

Code: STAN53

<p>How do multiple variables interact and influence each other? This course introduces multivariate analysis - a set of tools for exploring relationships between several variables at once.</p><p>In fields like genetics, the number of variables often exceeds the number of observations.This course teaches specialised techniques for analysing multivariate and particularly high-dimensional data - a growing challenge in modern statistics.</p><p>The course covers:</p><ul><li>matrix algebra and the multivariate normal distribution</li><li>singular value decomposition and its geometric interpretation</li><li>principal component analysis, including functional formulations</li><li>factor analysis and clustering techniques</li><li>prediction theory with high-dimensional predictors</li><li>penalised regression methods</li><li>sparse matrices</li><li>linear discriminant analysis</li><li>large-scale inference.</li></ul>

Entry requirements

90 credits in Statistics, or the equivalent.

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.

• Statistics: High-dimensional Data Analysis

  Lund University

  Start date: 2 November 2026

  End date: 17 January 2027

  Pace of study: 50 %