International courses to empower researchers everywhere
Our courses give participants the knowledge and the tools they need to tackle multivariate data analysis with confidence.
Our presenters combine statistical expertise with a knowledge and passion for ecology. Courses are delivered either on-line or in-person, with live lectures, open Q&A, and hands-on practical sessions that use a wide variety of examples.
Topics are presented in a conceptually accessible manner, with special emphasis on the interpretation of results. No prior background in statistics is assumed and there is no need to purchase software to participate. Our aim is to meet people’s needs, wherever they are on their research journey. Participants tend to emerge triumphant, replete with novel insights into their own datasets.
PRIMER-e's Standard Terms & Conditions for Courses
All Courses
PRIMER 7
Available in English and Spanish
Available in English and Spanish
This course will provide an intensive and extensive overview of statistical methods in non-parametric analysis of multivariate data, encapsulated in the software: PRIMER 7. Core multivariate routines covered in this course include: pre-treatment of data; definitions of (dis)similarity; clustering analysis (CLUSTER); ordination by principal components analysis (PCA) and non-metric multi-dimensional scaling (nMDS); permutation tests on similarity matrices for structured (ANOSIM, RELATE) and unstructured (SIMPROF) cases; linking biotic patterns to environmental (or other) data (BIO-ENV, BEST); biodiversity indices, including taxonomic distinctness; graphical tools for effective presentation of results, and more.
PERMANOVA +
Available in English and Spanish
This course gives a fundamental understanding of how to analyse and gain insights from multivariate data using the software PERMANOVA+. Participants will analyse multivariate data in response to complex sampling/experimental designs or continuous (e.g., environmental) variables. This is achieved through a partitioning of variation on the basis of a resemblance measure of choice, with rigorous inferences via carefully constructed permutation algorithms. These tools provide formal (semi-parametric) models, tests and predictions for multivariate (or univariate) ecological (and other) systems that are over-parameterised (i.e., have too many variables) and/or that demonstrate substantial non-normality. Routines covered include PERMANOVA, PERMDISP, DISTLM, dbRDA, PCO, CAP, graphical tools for visualisation, and more.
PRIMER / PERMANOVA Essentials
Available in English
This course provides participants with a broad understanding of an important suite of essential methods available in PRIMER with PERMANOVA+. First, participants will explore the properties of multivariate data, the use of transformations and standardisations, and the qualities associated with different resemblance measures. Next, the core techniques of cluster analysis and ordination (PCA, MDS) will be discussed, followed by non-parametric (rank-based) hypothesis tests using the ANOSIM, RELATE and BEST routines in PRIMER. This course also covers fundamental aspects of semi-parametric methods, including PERMANOVA for multi-factor experimental designs, and tests for homogeneity of dispersions using PERMDISP. The DISTLM and dbRDA routines, relating species to environmental (or other) data, will also be covered broadly in this course, along with graphical tools for effective presentation of results, such as matrix displays, segmented bubble plots, and more.