The Laboratory of Marine Biotechnology, Universiti Putra Malaysia, Serdang, Malaysia

How to Register

For further information please download and read the workshop documents listed in the blue box above. To register, please send your completed registration form to the PRIMER-e office at: [email protected]. Please send a separate individual registration form for each participant and contact the PRIMER-e office directly if you wish to receive a single invoice for multiple registrations. For information regarding on-site logistics contact the local organiser: Ms. Fadzillah Abdul Razak ([email protected]; [email protected]).

Workshop Details

PRIMER version 7 Workshop

Dr Paul Somerfield

Participants will engage in a mixture of informative lectures on key topics and computer lab sessions on literature data sets. Participants can also discuss and analyse their own data sets in consultation with the lecturer, with dedicated time for this provided on the Friday.

This workshop will provide an intensive and extensive overview of statistical methods in non-parametric analysis of multivariate data, using PRIMER version 7. It will cater both to those who are new to PRIMER and to those who are “old hands”, but have not yet had a chance to get up to speed with the latest developments in version 7.

As well as covering the new methods in PRIMER version 7, the core basic multivariate routines will also all be fully discussed, e.g. pre-treatment of data; definitions of similarity; clustering; ordination by principal components (PCA), non-metric (and metric) multi-dimensional scaling (MDS); permutation tests on similarity matrices for structured designs (ANOSIM, RELATE) and unstructured cases (SIMPROF); emphasis on species analyses; linking community to abiotic data (BEST); biodiversity indices; bootstrap average plots (with approximate region estimates) and the many graphical tools available for effective presentation of results. Non-parametric statistics and permutation tests make the methods intuitively simple to understand so no prior background in statistics is assumed.