Statistics: High-dimensional Data Analysis

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.

The course covers:

• matrix algebra and the multivariate normal distribution
• singular value decomposition and its geometric interpretation
• principal component analysis, including functional formulations
• factor analysis and clustering techniques
• prediction theory with high-dimensional predictors
• penalised regression methods
• sparse matrices
• linear discriminant analysis
• large-scale inference.

You’ll combine theoretical learning with hands-on exercises using real datasets. The course encourages critical thinking and practical application of multivariate methods in high-dimensional settings.

After completing the course, you’ll be able to conduct your own analyses of multivariate and high-dimensional data. You’ll also be well prepared for further studies or research in statistics and data science.

Prerequisites

90 credits in Statistics, or the equivalent.

Selection criteria

Seats are allocated according to: ECTS (HPAV): 100 %.

Tuition fees for non-EU/EEA citizens

Citizens of countries outside:

• The European Union (EU)
• The European Economic Area (EEA) and
• Switzerland

are required to pay tuition fees. You pay an instalment of the tuition fee in advance of each
semester.

Tuition fees, payments and exemptions

Full programme/course tuition fee: SEK 18,750
First payment: SEK 18,750

Convert currency – xe.com

Note that you may also need to pay an application fee, or provide proof of exemption.

Application fee

No tuition fees for citizens of the EU, EEA and Switzerland

There are no tuition fees for citizens of the European Union (EU), the European Economic Area (EEA) and Switzerland.