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Course pre-requisites can be found here. All the raw files and code can be found here. Click ‘Clone or Download’ near the top right and then ‘Download ZIP’ if you want an offline copy of everything.

As this module will be delivered online please install Zoom and Slack to access the videos and interactive components of the course. All the Zoom links to the meeting will be posted to the Slack #zoom-links channel.

Please note that the course will be recorded so that attendees in different time zones can catch up on material.

Tuesday

Introduction to SIA data and revision of basic statistical and R concepts

Time Class
9:30-10:30 Introduction: why use a SIMM? (AJ & AP)
10:30-10:45 Coffee break
10:45-11:45 Revision of likelihood and regression (AP)
11:45-12:00 Break
12:00-13:00 Guided practical: Revision of important R concepts (AP)
13:00-14:00 Lunch
14:00-15:00 Guided practical: Intro to SI data and biplots (AJ)
15:00-15:30 Coffee break
15:30-17:00 Guided Practical: Simple linear models to explain SIA data (AJ)

Wednesday

Introduction to Bayes and SIMMs

Time Class
9:30-10:30 An introduction to Bayesian statistics (AP)
10:30-10:45 Coffee break
10:45-11:45 Guided practical: R, JAGS, and linear regression (AP)
11:45-12:00 Break
12:00-13:00 Differences between regression models and SIMMs (AP)
13:00-14:00 Lunch
14:00-15:00 Guided practical: intro to simmr (AP)
15:00-15:30 Coffee break
15:30-17:00 Practical: options are (1) run your data through AJ’s plots from yesterday, or (2) get your data to run in simmr, or (3) go back and learn ggplot2 from this script

Thursday

simmr / MixSIAR

Time Class
9:30-10:30 The statistical model behind simmr (and SIAR) (AP)
10:30-10:45 Coffee break
10:45-11:45 Guided Practical: using MixSIAR and incorporating prior information in simmr (AP)
11:45-12:00 Break
12:00-13:00 Dos and don’ts of using mixing models with discussion (AJ)
13:00-14:00 Lunch
14:00-15:00 Dos and don’ts continued (AJ)
15:00-15:30 Coffee break
15:30-17:00 Practical: Source grouping, when and how? (AJ)

Friday

Source grouping, SIBER, and (new!) cosimmr

Time Class
9:30-10:30 Creating and understanding Stable Isotope Bayesian Ellipses (SIBER) (AJ)
10:30-10:45 Coffee break
10:45-11:45 Guided Practical: Using SIBER to compare populations using ellipses (AJ)
11:45-12:00 Break
12:00-13:00 Practical: pick a MixSIAR example and look at the manual (AP & AJ)
13:00-14:00 Lunch
14:00-15:00 Introduction to cosimmr and practical (EG & AP)
15:00-15:30 Coffee break
15:30-17:00 Guided Practical: Using SIBER to compare communities using convex hulls (AJ)