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Advancing in statistical modelling for evolutionary biologists and ecologists using R (ADVR08R)

21st January 2019 - 25th January 2019

£400.00
Advancing in statistical modelling for evolutionary biologists and ecologists using R (ADVR08R)

Event Date

Monday, January 21st, 2019

Course Format

Pre-Recorded

About This Course

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 the way you will gain in depth experience in data ‘wrangling’, data and model visualisation and plotting, as well as exploring and understanding model diagnostics. Classes will comprises of a mixture of lectures and practicals designed to either build required skills for future modules or to perform a family of analyses that is frequently encountered in the biological literature.

Intended Audiences

The course is aimed at biologists with a basic to moderate knowledge in R. The course content is designed to bridge the gap between basic R coding and more advanced statistical modelling.

Venue

Venue – PR statistics head office, 53 Morrison Street, Glasgow, G5 8LB – Google map

Course Details

Last Up-Dated – 25:01:2019

Duration – Approx. 35 hours

ECT’s – Equal to 3 ECT’s

Language – English

Teaching Format

 

 

 

A laptop/personal computer with a working version or R and RStudio installed. R and RStudio are supported by both PC and MAC and can be downloaded for free by following these links

https://cran.r-project.org/

Download RStudio

UNSURE ABOUT SUITABLILITY THEN PLEASE ASK oliverhooker@prstatistics.com

Assumed quantitative knowledge

We will assume only a minimal amount of familiarity with some general statistical and mathematical concepts. These concepts will arise when we discuss statistics and data analysis. Anyone who has taken any undergraduate (Bachelor’s) level course on (applied) statistics can be assumed to have sufficient familiarity with these concepts.

Assumed computer background

Familiarity with R. Ability to import/export data, manipulate data frames, fit basic statistical models & generate simple exploratory and diagnostic plots. Relative newcomers to programming in R will be provided (by the instructors) with some introductory exercises to complete prior to the course. This will introduce some of the core features of R and RStudio before the course starts.

Equipment and software requirements

A laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs, Macs, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/.

All the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed, and a full list of required packages will be made available to all attendees prior to the course.

A working webcam is desirable for enhanced interactivity during the live sessions, we encourage attendees to keep their cameras on during live zoom sessions.

Although not strictly required, using a large monitor or preferably even a second monitor will improve he learning experience

PLEASE READ – CANCELLATION POLICY

Cancellations/refunds are accepted as long as the course materials have not been accessed,.

There is a 20% cancellation fee to cover administration and possible bank fess.

If you need to discuss cancelling please contact oliverhooker@prstatistics.com.

If you are unsure about course suitability, please get in touch by email to find out more oliverhooker@prstatistics.com

COURSE PROGRAMME

Day 1 – Approx. 7 hours

Course introduction; techniques for data manipulation, aggregation, and visualisation; introduction to linear regression. Packages: {tidyr}, {dplyr}, {ggplot2}

Day 2 – Approx. 7 hours

Linear models (diagnostics, collinearity, scaling, plotting fitted values); fitting and interpreting interaction terms; model selection and simplication; general linear models and ANCOVA.
Packages: {stats}, {car}

Day 3 – Approx. 7 hours

Generalized linear models (logistic and Poisson regression); predicting using model objects and visualizing model fits. Packages: {broom}, {visreg}, {ggplot2}

Day 4 – Approx. 7 hours

Mixed effects models in theory and practice; visualising fixed and random effects.
Packages: {lme4}, {broom}, {ggplot2}, {sjPlot}

Day 5 – Approx. 6 hours

Fitting nonlinear functions (polynomial & mechanistic models); brief introduction to more advanced topics & combining methods (e.g., generalised linear mixed effects, nonlinear mixed effects, and zero-inflated and zero-altered models). Packages: {nlsTools}

Course Instructor

 

Dr. Antoine Becker-Scarpitta

Works at – University of Helsink
Teaches – Multivariate analysis of ecological communities in R with the VEGAN package (VGNR03)
Antoine is a plant community ecologist working as a postdoctoral researcher at the University of Helsinki and as a postdoctoral fellow at the Institute of Botany of the Academy of the Czech Republic. Antoine holds a degree in Conservation Biology from the University of Paris-Sud-Orsay, and from the Natural History Museum of Paris, he obtained his PhD in Biology/Ecology from the University of Sherbrooke (Canada). Antoine’s research focuses on the temporal dynamics of biodiversity with a particular focus on the forest and Arctic vegetation. Antoine has taught community ecology, plant ecology and evolution, linear and multivariate statistics assisted on R.

Details

Start:
21st January 2019
End:
25th January 2019
Cost:
£400.00
Event Category:

Venue

PR statistics head office
53 Morrison Street
Glasgow, Scotland G5 8LB United Kingdom
+ Google Map
Phone
07966500340
View Venue Website