It documents Linear Mixed Models with Random Effects using R. The code loads necessary libraries, simulates data from simulation, fits loggistic distributions to simulated and real data, and adds random effects lmer().

This material corresponds to Week 10 of the labs and demos for Bio 4259F (Undergraduate) and Bio 9915A (Graduate) at Western University.

It documents Poisson regression activities using R. The code loads necessary libraries, simulates data from Poisson distributions, fits Poisson distributions to simulated and real data, and performs Poisson regression analyses on example datasets (Soay sheep fitness and warpbreaks) from Beckerman et al. 2017 Chapter 7.

Week 6 of the labs and demos for Bio 4259F (Undergraduate) and Bio 9915A (Graduate) at Western University. The workflow applied here is an adaptation of that paper’s protocol, designed to guide students step-by-step through a technical data-exploration process: checking data quality, identifying outliers, diagnosing collinearity, simplifying models, and visualizing relationships to ensure that final statistical analyses are robust and interpretable.

This material corresponds to Week 4 of the labs and demos for Bio 4259F (Undergraduate) and Bio 9915A (Graduate) at Western University.

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