Multivariate Statistics deals with joint distributions of several random variables. This course introduces the basic concepts and provides an overview over classical and modern methods of multivariate statistics. We will consider the theory behind the methods as well as their applications.
After the course, you should be able to: - describe the various methods and the concepts and theory behind them - identify adequate methods for a given statistical problem - use the statistical software "R" to efficiently apply these methods - interpret the output of these methods
Visualization / Principal component analysis / Multidimensional scaling / The multivariate Normal distribution / Factor analysis / Supervised learning / Cluster analysis
The course will be based on class notes and books that are available electronically via the ETH library.
Prerequisites / Notice
Target audience: This course is the more theoretical version of "Applied Multivariate Statistics" (401-0102-00L) and is targeted at students with a math background.
Prerequisite: A basic course in probability and statistics.
Note: The courses 401-0102-00L and 401-6102-00L are mutually exclusive. You may register for at most one of these two course units.
Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
Language of examination
A repetition date will be offered in the first two weeks of the semester immediately consecutive.
Additional information on mode of examination
written 120 minutes
No public learning materials available.
Only public learning materials are listed.
No information on groups available.
There are no additional restrictions for the registration.