401-0102-00L Applied Multivariate Statistics
Semester | Spring Semester 2016 |
Lecturers | M. H. Maathuis |
Periodicity | two-yearly recurring course |
Language of instruction | English |
Abstract | Multivariate Statistics studies methods to analyze data on several random variables simultaneously. This course introduces the basic concepts and provides an overview of classical and modern methods of multivariate statistics, with an emphasis on applications. |
Objective | After the course, you should be able to: - describe the various methods and the concepts 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 / Classification / Cluster analysis |
Lecture notes | None |
Literature | We will use parts of the book "Introduction to Statistical Learning: With Applications in R" by Gareth, Witten, Hastie and Tibshirani. An electronic version is available from the ETH library. |
Prerequisites / Notice | This course is targeted at students with a non-math background. Prerequisite: A basic course in probability and statistics. |