ECTS credits

2 ECTS

Course parameters

Language: English

Level of course: PhD course

Time of Year: 19-23 September 2022

Capacity limits: 30

No. of contact hours: 30 (plus ~10 hours of reading & preparation time and ~10 hours completing computer assignments,)

Objectives of the course

The aim of the course is to provide an introduction to the analysis of multivariate data arising from observation and experimental studies with the R statistical software.

Learning outcomes and competences

After completing the course, participants will:

1. have a good introductory understanding of the main approaches used in the analysis of multivariate data sets
2. be able to choose an appropriate method to use to analyse a data set
3. understand how to use restricted permutation tests with constrained ordination methods to test the effects of predictor variables or experimental treatments
4. be able to use the R statistical software to analyse multivariate data

Compulsory programme

Active participation in the course including attendance at lectures and completion of computer-based classes and exercises. A learn by teaching approach will be used for the computer-based assessments, where each participant will be expected to, as part of a small group, demonstrate their approach to the analysis of a problem data set from the previous day. Completion of short, computer-based assessments testing their understanding of a topic and the practical skills taught.

Course contents

The course is based on a series of lectures and computer based practical classes led by an international expert in the analysis of multivariate data, who is also one of the senior developers of the vegan R package and the creator of the permute R package.

The course covers the following topics:

• An introduction to multivariate data and their analysis
• Dissimilarity and dissimilarity coefficients
• Cluster Analysis
• Unconstrained ordination
  • Principal Components Analysis
  • Correspondence Analysis
  • Principal Coordinates Analysis
  • Non-metric Multidimensional Scaling
• Constrained ordination
  • Redundancy Analysis
  • Canonical Correspondence Analysis
  • Distance-based Redundancy Analysis
  • PERMANOVA and PERMDISP
• Statistical testing using permutation tests
• The future of multivariate data analysis
  • Introduction to recently-developed latent variable approaches to ordination

Prerequisites

This course is suitable for Phd students (including senior thesis-based masters students) and researchers working with multivariate data sets in biology (inter alia animal science, ecology, agriculture, microbial ecology/microbiology). Some basic prior knowledge of R is required.

Name of course leader

Gavin Simpson Assistant Professor, Department of Animal Science, Aarhus University gavin@anis.au.dk

Name of lecturers

Gavin Simpson Assistant Professor, Department of Animal Science, Aarhus University gavin@anis.au.dk

Literature

Open access teaching resources prepared by the course leader will be supplemented by original literature (papers). Electronic copies of the open access teaching resources will be provided to each participant prior to the commencement of the course.

Course homepage

https://gavinsimpson.github.io/au-multivariate-stats/

Course assessment

The course will be assessed through a series of guided, short computer-based assessments involving multiple choice and short-answer questions on a problem data set or topic. The learn by teaching presentations will form part of the assessment.

Provider

The course is provided by the Department of Animal Science, Aarhus University.

Special comments on this course

Participants will be expected to provide their own laptop computer to complete the computer-based elements of the course, including the assessments. Instructions on installing R/RStudio and required packages will be provided to participants prior to commencement of the course.

Time

19-23 September 2022.

Five days of teaching in a single week long block. Classes held 09.00-16.00 daily.

Place

The course will be held at AU Campus Viborg, Dept. Animal Science, Blichers Allé 20, DK-8830 Tjele, Denmark. Accomodation (if needed and at participants own expense) can be found in Viborg. AU Campus Viborg is located  approximately 14 km from the city of Viborg and is served by a number of bus services.

Registration

Open from 1 March 2022 to 30 June 2022 via e-mail to Julie Sloth Jensen, e-mail: jsj@anis.au.dk, including a brief application with title and start year of PhD project, scientific keywords, address and contact information.

All applicants will receive information regarding participation no later than 1 July 2022 (but typically within 1 week of receipt of your registration e-mail).