401-6102-00L Multivariate Statistics
|Semester||Spring Semester 2020|
|Periodicity||two-yearly recurring course|
|Course||Does not take place this semester.|
|Language of instruction||English|
|Abstract||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.|
|Objective||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
|Content||Visualization / Principal component analysis / Multidimensional scaling / The multivariate Normal distribution / Factor analysis / Supervised learning / Cluster analysis|
|Literature||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.