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53 Morrison Street
Glasgow, G5 8LB United Kingdom

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November 2018
£520.00 - £890.00

Structural Equation Modelling for Ecologists and Evolutionary Biologists (SEMR02)

19th November 2018 - 23rd November 2020
PR statistics Head Office, 53 Morrison Street
Glasgow, G5 8LB United Kingdom

Course Overview: Course Overview: The course is a primer on structural equation modelling (SEM) and confirmatory path analysis, with an emphasis on practical skills and applications to real-world data. Structural equation modelling is a rapidly growing technique in ecology and evolution that unites multiple hypotheses in a single causal network. It provides an intuitive graphical representation of relationships among variables, underpinned by well-described mathematical estimation procedures. Several advances in SEM over the past few years have expanded its utility for…

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January 2019

Advancing in statistical modelling for evolutionary biologists and ecologists using R (ADVR08)

21st January 2019 - 25th January 2021
PR statistics Head Office, 53 Morrison Street
Glasgow, G5 8LB United Kingdom

Course Overview: This course will provide an introduction to working with real-life data typical of those encountered in the field of evolutionary biology and ecology. The course will be delivered by Dr. Luc Bussiere, Dr. Tom Houslay and Dr. Ane Timenes Laugen who are all practicing academics in the field of evolutionary biology.  This five day course will consist of series of modules (each lasting roughly half a day) covering model selection and simplification, generalised linear models, mixed effects models,  and non-linear models. Along…

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April 2019

Machine learning using R (MLUR01)

8th April 2019 - 12th April 2021
PR statistics Head Office, 53 Morrison Street
Glasgow, G5 8LB United Kingdom

Course Overview: This workshop will provide attendees with the opportunity to learn how to use machine learning to analyze data coming from diverse data domains and scientific disciplines and without necessarily prior knowledge of the scientific discipline where the data are coming from. Attendees will learn how to use R and several R packages including classification and regression trees, ensembles and bagging, random forests, neural networks, and boosting (learning from mistakes). These techniques will be used for data classification, determining…

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