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ONLINE COURSE – Bayesian hierarchical modelling using R (IBHM05)
4th December 2020 - 11th December 2020
£225.00
Event Date
Friday, December 4th, 2020
Course Format
This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.
Course Program
TIME ZONE – UTC+2 – however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an additional 1/2 days support after the official course finish date (please email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you).
Course Details
This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.
TIME ZONE – GMT – however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an additional 1/2 days support after the official course finish date (please email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you).
Intended Audiences
Venue
Delivered remotely
Course Information
Time zone – GMT
Availability – 20 places
Duration – 3 days
Contact hours – Approx. 15 hours
ECT’s – Equal to 1 ECT’s
Language – English
Teaching Format
There will be morning lectures based on the modules outlined in the course timetable. In the afternoon there will be practicals based on the topics covered that morning. Data sets for computer practicals will be provided by the instructors, but participants are welcome to bring their own data.
All sessions will be video recorded and made available to all attendees as soon as possible.
Attendees in different time zones will be able to join in to some of these live broadcasts, even if all of them are not convenient times. By joining any live sessions that are possible, this will allow attendees to benefit from asking questions and having discussions, rather than just watching prerecorded sessions.
At the start of the first day, we will ensure that everyone is comfortable with how Zoom works, and we’ll discuss the procedure for asking questions and raising comments.
Although not strictly required, using a large monitor or preferably even a second monitor will make the learning experience better, as you will be able to see my RStudio and your own RStudio simultaneously.
All the sessions will be video recorded, and made available immediately on a private video hosting website. Any materials, such as slides, data sets, etc., will be shared via GitHub.
Assumed quantitative knowledge
A basic understanding of regression methods and generalised linear models.
Assumed computer background
Familiarity with R. Ability to import/export data, manipulate data frames, fit basic statistical models & generate simple exploratory and diagnostic plots.
Equipment and software requirements
A laptop/personal computer with a working version or R, RStudio, JAGS and stan installed. All are supported by both PC and MAC and can be downloaded for free by following these links.
https://cran.r-project.org/
http://mcmc-jags.sourceforge.net
http://mc-stan.org/
It is essential that you come with all necessary software and packages already installed (you will be sent a list of packages prior to the course) internet access may not always be available.
UNSURE ABOUT SUITABLILITY THEN PLEASE ASK oliverhooker@prstatistics.com
Assumed quantitative knowledge
Coming soon..
Assumed computer background
Coming soon..
Equipment and software requirements
Attendees will need to install/update R/RStudio and various additional R packages.
This can be done on Macs, Windows, and Linux.
R – https://cran.r-project.org/
RStudio – https://www.rstudio.com/products/rstudio/download/
PLEASE READ – CANCELLATION POLICY
Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.
COURSE PROGRAMME
Day 1
Approx 8 hours
Module 3: Simple hierarchical regression models
Module 4: Hierarchical models for non-Gaussian data
Practical: Fitting hierarchical models
Friday 27th November
Classes from 09:30 to 17:30
Module 3: Simple hierarchical regression models
Module 4: Hierarchical models for non-Gaussian data
Practical: Fitting hierarchical models
Friday 4th December
Classes from 09:30 to 17:30
Module 5: Hierarchical models vs mixed effects models
Module 6: Multivariate and multi-layer hierarchical models
Practical: Advanced examples of hierarchical models
Friday 11th December
Classes from 09:30 to 17:30
Module 7: Shrinkage and variable selection
Module 8: Hierarchical models and partial pooling
Practical: Shrinkage modelling
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.