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Lecture "Applied Multivariate Statistics" 2011/2012

In order to enable (1) studying from home, (2) watching the lectures again at a later time (e.g. preparation for the exam, data analysis for thesis) and (3) following the lecture from outside of university, I make this lecture publicly available including all course materials. Note that all material comes without guarantee!

You can download the course schedule and the literature list. The slides are provided cumulatively i.e. slides for a session contain all slides of the previous sessions. Hence, in order to obtain the full set, you only need to download the slides of Session 6.

In case you have any comments regarding content, please feel free to contact me.

Session 1: Introduction and revisiting univariate statistics

Contents: Exploratory data analysis, statistical modelling, comparison of central tendency, linear regression model with diagnostics

Materials: Lecture slides (with notes), R starter script with exercises, possum data set, tannin data set and video from the lecture. A complete R script with all solutions to the exercises can be found here.

Session 2: Linear Modelling

Contents: Multiple linear regression, collinearity, goodness of fit and variable selection, relative importance of variables.

Materials: Lecture slides (with notes), R script with exercises and video from the lecture. Due to a technical issue (flat battery) no audio was recorded for the last 30 minutes of the lecture. 

Session 3: GLMs and multivariate Hypothesis testing

Contents: Generalized linear models (GLMs), Introduction multivariate data analysis and multivariate hypothesis tests. 

Materials: Lecture slides (with notes), R scripts with exercises and video from the lecture.

Session 4: MANOVA and Resemblence metrics

Contents: Hotelling T2, MANOVA, Jaccard index, Bray-Curtis index and Euclidean distance.

Materials: Lecture slides (with notes) and R script with exercises (one script from Session 3 will be used again). No video available. 

Session 5: PERMANOVA and Classification

Contents: Visualising distances, PERMANOVA and Cluster analysis.

Materials: Video and lecture slides (with notes). The script from Session 4 will be used again for the exercises, for the solution see here. Additional R script for figures, visualisation tools. 

Session 6: Ordination

Contents: Introduction, Principal Component Analysis and Non-metric multidimensional Scaling

Materials: Video, lecture slides (with notes) and R script with exercises.