STATISTICS COURSE 'ADVANCING IN R'
A repeat of the course titled 'ADVANCING IN R' has been arranged for 30th November – 4th December 2015
The content designed to bridge the gap between basic R coding and more advanced statistical modelling. The course is aimed at PhD students and post docs (although people at any stage of their career are welcome) with basic to moderate knowledge in R.
It will be held at SCENE (Scottish Center for Ecology and the Natural Environment), Glasgow, United Kingdom.
Course content is as follows and is based on biological and ecological data sets
Module 1 Data manipulation & visualization using {dplyr} and {ggplot}
Module 2 Univariate regression, diagnostics & plotting fits
Module 3 Adding additional continuous predictors (multiple regression); scaling & collinearity
Module 4 Adding factorial (categorical) predictors & incorporating interactions (ANCOVA)
Module 5 Model selection & simplification (likelihood ratio tests, AIC)
Module 6 Predicting on the basis of coefficients
Module 7 Mixed effects model in theory and in practice
Module 8 Generalised linear models in theory and practice
Module 9 Nonlinear models (polynomial & mechanistic models)
Module 10 Mored advanced topics & combinig methods (e.g. nonlinear mixed effect models (NLME) & generalised linear mixed effects models (GLMM).
Cost is £460 for the 5 days including lunches and refreshments or £635 for an all-inclusive option which includes the addition of accommodation, all meals and refreshments.
There is also the possibility (depending on time) to have casual one to one discussion regarding your own research so you are encouraged to bring data with you however this cannot be guaranteed.
For further details or questions please email [log in to unmask] or visit www.prstatistics.co.uk - upcoming courses; ANALYSIS OF STABLE ISOTOPE DATA USING SIA-R; AN INTRODUCTION TO USING GIS IN ECOLOGICAL FIELD STUDIES; APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS; SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R
Please feel free to distribute this among colleagues if you think it is suitable
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