index.qmd

# Motivation {.unnumbered}

This is an online book adapted from [previous course notes](https://github.com/njtierney/greta-course-notes) we have provided for teaching `greta`. While the [greta website](https://greta-stats.org/index.html) provides many examples of fitting models (for example, the [eight schools](https://greta-stats.org/articles/analyses/eight_schools.html) vignette), this book aims to provide further guided instructions on how to get up and running with `greta`. The rough structure of the book is to provide information on the following:

This book is designed for those who want to learn how to do Bayesian modelling using the `greta` software. We assume users have the following background/experience:

-   Familiarity with R

-   Experience using linear models

-   A rudimentary understanding of Bayesian inference

After this course you will be able to:

-   Fit and predict from Bayesian generalised linear models in greta

-   Check model convergence and fit (including prior and posterior predictive checks)

-   Summarise MCMC outputs

-   Be able to fit more advanced models including mixture and hierarchical models

-   Create visualisations and tables of the model outputs for use in understanding model fit and for publication.

This book will also provide details on the following:

-   installation instructions and troubleshooting

-   technical details of the internals of greta

-   Adding extensions to greta

As this book develops, materials from here will likely be moved into the greta website.