Multivariate Statistics in Ecology and Quantitative Genetics SS 2017

Lecture with Exercises (Vorlesung mit Übung)


Dirk Metzler and Noémie Becker

Time and rooms

10. July to 28. July
Lecture: Every day (Mo to Fr) from 9:00 to 10:30
Exercises: Plan the rest of each Tuesday to Friday for working on the exercises. Exercise sessions on these days will usually be from 11 to 11:30 am and from 3:30 to 5:00 pm.
Rooms for the lecture: Mondays, Wednesdays and Fridays: C00.013
Tuesdays and Thursdays: D00.013
Exception: Tuesday, 18. July: E02.023
Exercises: While working on the exercise assignments you can sit in lab room C00.027.


The make-up exam will be on 14. September between 8:00 and 10:00 am in the grand lecture hall N 00.001 of the biomedical center (green building, GroƟhaderner Str. 9; together with Bachelor's students who write their statistics make-up exam). To take the make-up exam you need to register by e-mail to Dirk Metzler before 4. September. You will have 90 minutes to answer the questions. Participants can bring non-programmable pocket calculators an their personal assortment of formulas on an A4 sheet. This A4 can have any contents on both sides BUT ONLY IN YOUR OWN HANDWRITING! (no copy, not print-out, not another person's handwriting) Please note: If you fully attend the course (which is required to get the ECTS points) you will need the time between the 11 a.m. and 5 p.m. to solve exercises, which will be given in the morning lectures and discussed in the afternoon courses.


Basic knowledge of statistics. If you are not already familiar with the free R software, it may be a good idea to install it on your computer and get a bit familiar with it before the course starts. Some examples (data file FinchesSulloway.txt), R tutorial, Martin's introductory R course.


In the exercises you will practice to analyse data with the methods listed below using the R software. We will discuss the interpretations of the results and problems that may arise during the analysis. In the lectures we will explain the theoretical concepts behind the methods and show how these methods can be applied.

If you would like to discuss analyses of your own datasets during the course, please contact D. Metzler as soon as possible.

Language: English

Course material

  1. Basics on anova: slides
  2. Balanced design ANOVAs, parameter transformations: slides, R-script, exercises sheet 1, abcdx.txt, bp.txt
  3. Linear Models: slides, R commands for Darwin finches, Darwin finches data, exercises sheet 2, bacteria_trainig.txt, bacteria_predict.txt
  4. Generalized Linear Models: slides, exercise sheet 3, simulate_data4glm.R, TbDeerAndBoar.txt
  5. Hotellings T2-test slides, R-script, raspberry.csv, exercise sheet 4, grapes.txt
  6. Principal Component Analysis (PCA): slides, R-script, exercise sheet 5, HeightShoeWeight.txt, Countries.txt, EWU.txt
  7. PCA Regression: slides, R-script, RIKZGroups.txt
  8. Redundancy Analysis (RDA): slides, R-script, exercise sheet 6, HSWoutlier.txt, artificialFishes.txt,
  9. Correspondence Analysis (CA): slides, R-script, MexicanPlants.txt
  10. Canonical Correspondence Analysis (CCA): slides, R-script, exercise sheet 7
  11. Mixed-effects models slides, lme4a.R, mcmcglmm.R, exercise sheet 8, fruits.txt
  12. QTL Mapping slides, R-script, exercise sheet 9

Material will be added during the course. Here is the course material from 2016.


Last update: 25. July 2017