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Random experiments and probability
Random variables and distributions
Functions of random variables and limit theorems
Studies, data, and evidence
Analysis of variance examples
Markov chains, Gibbs sampling, and Metropolis–Hastings
Categorical data and the Dirichlet distribution
Bayesian hypotheses and model comparison
Bayesian linear regression
Introduction to generalised linear models
Standard errors, and models for counts
Underdispersion, positive responses, and quasi-likelihood
Paired comparisons, and how far a fit is from the data
Probability-integral residuals
Random slopes, and a binary mixed model
Marginal models, and two responses at once
Three species on one hillside
Dependence along a series