# 401-0102-00L  Applied Multivariate Statistics

 Semester Frühjahrssemester 2017 Dozierende F. Sigrist Periodizität jährlich wiederkehrende Veranstaltung Lehrsprache Englisch

 Kurzbeschreibung 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 and solving problems with the statistical software "R". Lernziel After the course, you are 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 Inhalt Visualization, multivariate outliers, the multivariate normal distribution, principal component analysis, multidimensional scaling, factor analysis, cluster analysis, classification, multivariate tests Skript None Literatur 1) "An Introduction to Applied Multivariate Analysis with R" (2011) by Everitt and Hothorn 2) "An Introduction to Statistical Learning: With Applications in R" (2013) by Gareth, Witten, Hastie and TibshiraniElectronic versions (pdf) of both books can be downloaded for free from the ETH library. Voraussetzungen / Besonderes This course is targeted at students with a non-math background. Requirements:==========1) Introductory course in statistics (min: t-test, regression; ideal: conditional probability, multiple regression)2) Good understanding of R (if you don't know R, it is recommended that you study chapters 1,2,3,4, and 5 of "Introductory Statistics with R" from Peter Dalgaard, which is freely available online from the ETH library)An alternative course with more emphasis on theory is "Multivariate Statistics" (401-0102-00L).401-0102-00L and 401-0102-99L are mutually exclusive. You can register for only one of these two courses.