Dear all, registrations are now open for the online Multivariate Data Analysis with R and vegan course. Dates: February 10-13, 2025. Course website: ( https://www.physalia-courses.org/courses-workshops/vegan/ ) Overview: This course will offer participants a practical introduction to some of the most useful functions available within vegan. We will focus on the use of ordination methods and on the use of restricted permutations to test a range of experimental designs.We will focus on when and how to use multivariate methods including unconstrained and constrained ordination (CCA, RDA, Constrained PCoA), as well as between-group tests such as PERMANOVA. We will cover concepts such as design- and model-based permutations and the exchangeability of samples in tests. We will also discuss the use of vegan to go beyond simply fitting a constrained ordination model, to diagnostics, plotting, etc. Who Should Attend? This course is suitable for PhD students (including senior thesis-based masters students) and researchers working with multivariate data sets in biology (inter alia ecology, animal science agriculture, microbial ecology/microbiology), with limited statistical knowledge but a willingness to learn more.Participants should be familiar with RStudio and have some fluency in programming R code, including being able to import, manipulate (e.g. modify variables) and visualise data. There will be a mix of lectures, and hands-on practical exercises throughout the course. Program Overview Monday: Intro to multivariate data, transformations, dissimilarity metrics Tuesday: Unconstrained ordination (PCA, PCoA, NMDS) Wednesday: Constrained ordination, PERMANOVA Thursday: Statistical inference with permutation tests For the full list of our courses and workshops, please visit: ( https://www.physalia-courses.org/courses-workshops/vegan/ ) Best regards, Carlo Carlo Pecoraro, Ph.D Physalia-courses DIRECTOR info@physalia-courses.org "info@physalia-courses.org" (to subscribe/unsubscribe the EvolDir send mail to golding@mcmaster.ca)