index.qmd

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title: "Course contents"
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[Daily schedule](topics/schedule)

## Day 1: Introduction, data simulation, discrete models

[Course Syllabus](PlanDeCoursBIO709.pdf)

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### Slides
* [Introduction to the course and location](slides/00_Introduction)
* [Data we'll be using](slides/01_Data)
* [Probability Distributions](slides/02_5_Distribution)

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### Exercises -- data simulation & discrete models
* [Catch a wild Distribution](topics/00_distributions)

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:::{.callout-warning}
### Monday night Stan installation session! 
You're free to proceed in this course using any modelling software you like. 
We will be using Stan, so if you want to follow along you'll need to have it installed also! To do so, follow the steps [in this vignette](https://mc-stan.org/cmdstanr/articles/cmdstanr.html#compiling-a-model). Make sure you can run the example (up to "Running MCMC") 

Please note that if you want help installing it, Andrew and Guillaume will be available on **Monday evening**. From Tuesday onwards we won't have time to pause to fix installation issues!
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## DAY 2: Intro to Stan and Regression

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### Slides
* [Bayesian and MCMC](slides/02_Bayesian)
* [Stan and HMC](slides/03_Stan)
* [Linear models](slides/04_Linear_model)

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### Exercises
* [Simulation and model fitting in Stan](topics/01_simulation)
* [Discrete predictors](topics/discrete_predictor)
* [Linear regression](topics/02_regression)

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## Day 3: Hierarchical models

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### Slides
* [Simple hierarchical models](slides/06_Simple_hierarchical_model)
* [Complex hierarchical models](slides/08_Complex_hierarchical_model)

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### Exercises

* [Intercept-Only Model (and tidybayes discussion)](topics/intercept_only)
* [Hierarchy on the intercept](topics/03_one_random_effect)
* [Hierarchy on the slope](topics/correlated_effects)

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## Day 4: Constrained models: Gaussian processes

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* [Slides](slides/09_Gaussian_process)

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* [A Practical demonstration in Stan](topics/04_gp)

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